Prebuilt rule reference
editPrebuilt rule reference
editThis section lists all available prebuilt rules.
To run machine learning prebuilt rules, you must have the
appropriate license or use a
Cloud deployment. All machine learning prebuilt rules are tagged with ML,
and their rule type is machine_learning.
| Rule | Description | Tags | Added | Version |
|---|---|---|---|---|
Indicates the creation of a scheduled task using Windows event logs. Adversaries can use these to establish persistence, move laterally, and/or escalate privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: System] |
None |
9 |
|
Indicates the update of a scheduled task using Windows event logs. Adversaries can use these to establish persistence, by changing the configuration of a legit scheduled task. Some changes such as disabling or enabling a scheduled task are common and may may generate noise. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: System] |
None |
9 |
|
Detects file creation events in the configuration directory for the APT package manager. In Linux, APT (Advanced Package Tool) is a command-line utility used for handling packages on (by default) Debian-based systems, providing functions for installing, updating, upgrading, and removing software along with managing package repositories. Attackers can backdoor APT to gain persistence by injecting malicious code into scripts that APT runs, thereby ensuring continued unauthorized access or control each time APT is used for package management. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
4 |
|
AWS Bedrock Detected Multiple Attempts to use Denied Models by a Single User |
Identifies multiple successive failed attempts to use denied model resources within AWS Bedrock. This could indicated attempts to bypass limitations of other approved models, or to force an impact on the environment by incurring exhorbitant costs. |
[Domain: LLM], [Data Source: AWS Bedrock], [Data Source: AWS S3], [Resources: Investigation Guide], [Use Case: Policy Violation], [Mitre Atlas: T0015], [Mitre Atlas: T0034] |
8.13.0 |
3 |
AWS Bedrock Detected Multiple Validation Exception Errors by a Single User |
Identifies multiple validation exeception errors within AWS Bedrock. Validation errors occur when you run the InvokeModel or InvokeModelWithResponseStream APIs on a foundation model that uses an incorrect inference parameter or corresponding value. These errors also occur when you use an inference parameter for one model with a model that doesn’t have the same API parameter. This could indicate attempts to bypass limitations of other approved models, or to force an impact on the environment by incurring exhorbitant costs. |
[Domain: LLM], [Data Source: AWS], [Data Source: AWS Bedrock], [Data Source: AWS S3], [Use Case: Policy Violation], [Mitre Atlas: T0015], [Mitre Atlas: T0034], [Mitre Atlas: T0046] |
8.13.0 |
3 |
AWS Bedrock Guardrails Detected Multiple Policy Violations Within a Single Blocked Request |
Identifies multiple violations of AWS Bedrock guardrails within a single request, resulting in a block action, increasing the likelihood of malicious intent. Multiple violations implies that a user may be intentionally attempting to cirvumvent security controls, access sensitive information, or possibly exploit a vulnerability in the system. |
[Domain: LLM], [Data Source: AWS Bedrock], [Data Source: AWS S3], [Resources: Investigation Guide], [Use Case: Policy Violation], [Mitre Atlas: T0051], [Mitre Atlas: T0054] |
8.13.0 |
3 |
AWS Bedrock Guardrails Detected Multiple Violations by a Single User Over a Session |
Identifies multiple violations of AWS Bedrock guardrails by the same user in the same account over a session. Multiple violations implies that a user may be intentionally attempting to cirvumvent security controls, access sensitive information, or possibly exploit a vulnerability in the system. |
[Domain: LLM], [Data Source: AWS Bedrock], [Data Source: AWS S3], [Resources: Investigation Guide], [Use Case: Policy Violation], [Mitre Atlas: T0051], [Mitre Atlas: T0054] |
8.13.0 |
4 |
Detects the use of the AWS CLI with the |
[Data Source: Elastic Defend], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control] |
None |
1 |
|
Identifies the creation of an AWS log trail that specifies the settings for delivery of log data. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Tactic: Collection] |
None |
207 |
|
Identifies the deletion of an AWS log trail. An adversary may delete trails in an attempt to evade defenses. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |
None |
210 |
|
Identifies suspending the recording of AWS API calls and log file delivery for the specified trail. An adversary may suspend trails in an attempt to evade defenses. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |
None |
209 |
|
Identifies an update to an AWS log trail setting that specifies the delivery of log files. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Cloudtrail], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Impact] |
None |
209 |
|
Identifies the deletion of an AWS CloudWatch alarm. An adversary may delete alarms in an attempt to evade defenses. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Resources: Investigation Guide], [Tactic: Defense Evasion] |
None |
209 |
|
Identifies the deletion of a specified AWS CloudWatch log group. When a log group is deleted, all the archived log events associated with the log group are also permanently deleted. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS CloudWatch], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Impact] |
None |
209 |
|
Identifies the deletion of an AWS CloudWatch log stream, which permanently deletes all associated archived log events with the stream. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS CloudWatch], [Use Case: Log Auditing], [Tactic: Impact], [Resources: Investigation Guide] |
None |
209 |
|
Identifies attempts to delete an AWS Config Service resource. An adversary may tamper with Config services in order to reduce visibility into the security posture of an account and / or its workload instances. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Resources: Investigation Guide], [Tactic: Defense Evasion] |
None |
209 |
|
Identifies an AWS configuration change to stop recording a designated set of resources. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |
None |
206 |
|
This rule detects the use of system search utilities like grep and find to search for AWS credentials inside a container. Unauthorized access to these sensitive files could lead to further compromise of the container environment or facilitate a container breakout to the underlying cloud environment. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |
None |
1 |
|
Identifies the deletion of an Amazon Relational Database Service (RDS) Aurora database cluster, global database cluster, or database instance. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Impact] |
None |
206 |
|
Detects when a single AWS resource is running multiple |
[Domain: Cloud], [Data Source: AWS], [Data Source: AWS EC2], [Data Source: AWS IAM], [Data Source: AWS S3], [Use Case: Threat Detection], [Tactic: Discovery] |
8.13.0 |
1 |
|
Identifies the first occurrence of a user identity in AWS using |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon EC2], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Credential Access] |
None |
3 |
|
Identifies AWS EC2 EBS snaphots being shared with another AWS account. EBS virtual disks can be copied into snapshots, which can then be shared with an external AWS account or made public. Adversaries may attempt this in order to copy the snapshot into an environment they control, to access the data. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Threat Detection], [Tactic: Exfiltration] |
8.13.0 |
2 |
|
Identifies disabling of Amazon Elastic Block Store (EBS) encryption by default in the current region. Disabling encryption by default does not change the encryption status of your existing volumes. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Tactic: Impact] |
None |
206 |
|
Identifies potential Traffic Mirroring in an Amazon Elastic Compute Cloud (EC2) instance. Traffic Mirroring is an Amazon VPC feature that you can use to copy network traffic from an Elastic network interface. This feature can potentially be abused to exfiltrate sensitive data from unencrypted internal traffic. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Exfiltration], [Tactic: Collection] |
None |
206 |
|
Identifies when a new SSH public key is uploaded to an AWS EC2 instance using the EC2 Instance Connect service. This action could indicate an adversary attempting to maintain access to the instance. The rule also detects the |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |
None |
1 |
|
Identifies a successful console login activity by an EC2 instance profile using an assumed role. This is uncommon behavior and could indicate an attacker using compromised credentials to further exploit an environment. An EC2 instance assumes a role using their EC2 ID as the session name. This rule looks for the pattern "i-" which is the beginning pattern for assumed role sessions started by an EC2 instance and a successful |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Tactic: Lateral Movement], [Tactic: Credential Access] |
None |
1 |
|
Identifies when an EC2 instance interacts with the AWS IAM service via an assumed role. This is uncommon behavior and could indicate an attacker using compromised credentials to further exploit an environment. For example, an assumed role could be used to create new users for persistence or add permissions for privilege escalation. An EC2 instance assumes a role using their EC2 ID as the session name. This rule looks for the pattern "i-" which is the beginning pattern for assumed role sessions started by an EC2 instance. This is a [building block](https://www.elastic.co/guide/en/security/current/building-block-rule.html) rule and does not generate alerts on its own. It is meant to be used for correlation with other rules to detect suspicious activity. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation], [Tactic: Persistence], [Rule Type: BBR] |
None |
2 |
|
Identifies when a single AWS resource is making |
[Domain: Cloud], [Data Source: AWS], [Data Source: AWS EC2], [Resources: Investigation Guide], [Use Case: Threat Detection], [Tactic: Discovery] |
None |
3 |
|
Identifies the creation of an AWS Elastic Compute Cloud (EC2) network access control list (ACL) or an entry in a network ACL with a specified rule number. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Network Security Monitoring], [Tactic: Persistence] |
None |
206 |
|
Identifies the deletion of an Amazon Elastic Compute Cloud (EC2) network access control list (ACL) or one of its ingress/egress entries. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies a change to an AWS Security Group Configuration. A security group is like a virtual firewall, and modifying configurations may allow unauthorized access. Threat actors may abuse this to establish persistence, exfiltrate data, or pivot in an AWS environment. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Network Security Monitoring], [Resources: Investigation Guide], [Tactic: Persistence], [Tactic: Defense Evasion] |
None |
207 |
|
An attempt was made to modify AWS EC2 snapshot attributes. Snapshots are sometimes shared by threat actors in order to exfiltrate bulk data from an EC2 fleet. If the permissions were modified, verify the snapshot was not shared with an unauthorized or unexpected AWS account. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Exfiltration], [Resources: Investigation Guide] |
None |
209 |
|
Identifies an attempt to export an AWS EC2 instance. A virtual machine (VM) export may indicate an attempt to extract or exfiltrate information. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Exfiltration], [Tactic: Collection] |
None |
206 |
|
Detects when an EFS File System or Mount is deleted. An adversary could break any file system using the mount target that is being deleted, which might disrupt instances or applications using those mounts. The mount must be deleted prior to deleting the File System, or the adversary will be unable to delete the File System. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Impact] |
None |
206 |
|
Identifies when an ElastiCache security group has been created. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies when an ElastiCache security group has been modified or deleted. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies when a user has disabled or deleted an EventBridge rule. This activity can result in an unintended loss of visibility in applications or a break in the flow with other AWS services. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Impact] |
None |
206 |
|
Identifies the deletion of an Amazon GuardDuty detector. Upon deletion, GuardDuty stops monitoring the environment and all existing findings are lost. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |
None |
206 |
|
An adversary with access to a set of compromised credentials may attempt to persist or escalate privileges by attaching additional permissions to user groups the compromised user account belongs to. This rule looks for use of the IAM |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation], [Tactic: Persistence], [Resources: Investigation Guide] |
8.13.0 |
3 |
|
An adversary with access to a set of compromised credentials may attempt to persist or escalate privileges by attaching additional permissions to compromised IAM roles. This rule looks for use of the IAM |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation], [Tactic: Persistence], [Resources: Investigation Guide] |
8.13.0 |
3 |
|
An adversary with access to a set of compromised credentials may attempt to persist or escalate privileges by attaching additional permissions to compromised user accounts. This rule looks for use of the IAM |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation], [Tactic: Persistence], [Resources: Investigation Guide] |
8.13.0 |
4 |
|
Identifies attempts to modify an AWS IAM Assume Role Policy. An adversary may attempt to modify the AssumeRolePolicy of a misconfigured role in order to gain the privileges of that role. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Privilege Escalation] |
None |
209 |
|
Identifies a high number of failed attempts to assume an AWS Identity and Access Management (IAM) role. IAM roles are used to delegate access to users or services. An adversary may attempt to enumerate IAM roles in order to determine if a role exists before attempting to assume or hijack the discovered role. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Credential Access] |
None |
210 |
|
This rule looks for use of the IAM |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Resources: Investigation Guide], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |
None |
1 |
|
Detects the creation of an AWS Identity and Access Management (IAM) user initiated by an assumed role on an EC2 instance. Assumed roles allow users or services to temporarily adopt different AWS permissions, but the creation of IAM users through these roles—particularly from within EC2 instances—may indicate a compromised instance. Adversaries might exploit such permissions to establish persistence by creating new IAM users under unauthorized conditions. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
1 |
|
AWS IAM Customer-Managed Policy Attached to Role by Rare User |
Detects when an AWS Identity and Access Management (IAM) customer-managed policy is attached to a role by an unusual or unauthorized user. Customer-managed policies are policies created and controlled within an AWS account, granting specific permissions to roles or users when attached. This rule identifies potential privilege escalation by flagging cases where a customer-managed policy is attached to a role by an unexpected actor, which could signal unauthorized access or misuse. Attackers may attach policies to roles to expand permissions and elevate their privileges within the AWS environment. This is a [New Terms](https://www.elastic.co/guide/en/security/current/rules-ui-create.html#create-new-terms-rule) rule that uses the |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Resources: Investigation Guide], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |
None |
1 |
Identifies the deactivation of a specified multi-factor authentication (MFA) device and removes it from association with the user name for which it was originally enabled. In AWS Identity and Access Management (IAM), a device must be deactivated before it can be deleted. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Resources: Investigation Guide], [Tactic: Impact], [Tactic: Persistence] |
None |
210 |
|
Identifies the creation of a group in AWS Identity and Access Management (IAM). Groups specify permissions for multiple users. Any user in a group automatically has the permissions that are assigned to the group. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
206 |
|
Identifies the deletion of a specified AWS Identity and Access Management (IAM) resource group. Deleting a resource group does not delete resources that are members of the group; it only deletes the group structure. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Tactic: Impact] |
None |
206 |
|
Identifies when an AWS IAM login profile is added to a user. Adversaries may add a login profile to an IAM user who typically does not have one and is used only for programmatic access. This can be used to maintain access to the account even if the original access key is rotated or disabled. This is a building block rule and does not generate alerts on its own. It is meant to be used for correlation with other rules to detect suspicious activity. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Rule Type: BBR] |
None |
2 |
|
Identifies AWS IAM password recovery requests. An adversary may attempt to gain unauthorized AWS access by abusing password recovery mechanisms. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Signin], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |
None |
206 |
|
Identifies the creation of an AWS Roles Anywhere profile. AWS Roles Anywhere is a feature that allows you to use AWS Identity and Access Management (IAM) profiles to manage access to your AWS resources from any location via trusted anchors. This rule detects the creation of a profile that can be assumed from any service. Adversaries may create profiles tied to overly permissive roles to maintain access to AWS resources. Ensure that the profile creation is expected and that the trust policy is configured securely. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
2 |
|
AWS IAM Roles Anywhere Trust Anchor Created with External CA |
Identifies when an AWS IAM Roles Anywhere Trust Anchor with an external certificate authority is created. AWS Roles Anywhere profiles are legitimate profiles that can be created by administrators to allow access from any location. This rule detects when a trust anchor is created with an external certificate authority that is not managed by AWS Certificate Manager Private Certificate Authority (ACM PCA). Adversaries may accomplish this to maintain persistence in the environment. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
2 |
Identifies when a user has updated a SAML provider in AWS. SAML providers are used to enable federated access to the AWS Management Console. This activity could be an indication of an attacker attempting to escalate privileges. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |
None |
207 |
|
Identifies the addition of a user to a specified group in AWS Identity and Access Management (IAM). |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Tactic: Credential Access], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
209 |
|
An adversary with access to a set of compromised credentials may attempt to persist or escalate privileges by creating a new set of credentials for an existing user. This rule looks for use of the IAM |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation], [Tactic: Persistence], [Resources: Investigation Guide] |
8.13.0 |
4 |
|
AWS KMS Customer Managed Key Disabled or Scheduled for Deletion |
Identifies attempts to disable or schedule the deletion of an AWS KMS Customer Managed Key (CMK). Deleting an AWS KMS key is destructive and potentially dangerous. It deletes the key material and all metadata associated with the KMS key and is irreversible. After a KMS key is deleted, the data that was encrypted under that KMS key can no longer be decrypted, which means that data becomes unrecoverable. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS KMS], [Use Case: Log Auditing], [Tactic: Impact] |
None |
106 |
Identifies when an AWS Lambda function is created or updated. AWS Lambda lets you run code without provisioning or managing servers. Adversaries can create or update Lambda functions to execute malicious code, exfiltrate data, or escalate privileges. This is a [building block rule](https://www.elastic.co/guide/en/security/current/building-block-rule.html) that does not generate alerts, but signals when a Lambda function is created or updated that matches the rule’s conditions. To generate alerts, create a rule that uses this signal as a building block. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Lambda], [Use Case: Asset Visibility], [Tactic: Execution], [Rule Type: BBR] |
None |
2 |
|
AWS Lambda Function Policy Updated to Allow Public Invocation |
Identifies when an AWS Lambda function policy is updated to allow public invocation. This rule specifically looks for the |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Lambda], [Use Case: Threat Detection], [Tactic: Persistence] |
None |
1 |
Identifies when an Lambda Layer is added to an existing Lambda function. AWS layers are a way to share code and data across multiple functions. By adding a layer to an existing function, an attacker can persist or execute code in the context of the function. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Lambda], [Use Case: Threat Detection], [Tactic: Execution] |
None |
2 |
|
Identifies a high number of failed authentication attempts to the AWS management console for the Root user identity. An adversary may attempt to brute force the password for the Root user identity, as it has complete access to all services and resources for the AWS account. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |
None |
207 |
|
Identifies a successful login to the AWS Management Console by the Root user. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Signin], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |
None |
209 |
|
Identifies the creation of a new Amazon Relational Database Service (RDS) Aurora DB cluster or global database spread across multiple regions. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Persistence] |
None |
206 |
|
Identifies the creation or modification of an AWS RDS DB instance to enable public access. DB instances may contain sensitive data that can be abused if shared with unauthorized accounts or made public. Adversaries may enable public access on a DB instance to maintain persistence or evade defenses by bypassing access controls. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Resources: Investigation Guide], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |
None |
2 |
|
An adversary with a set of compromised credentials may attempt to make copies of running or deleted RDS databases in order to evade defense mechanisms or access data. This rule identifies successful attempts to restore a DB instance using the RDS |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Defense Evasion] |
None |
207 |
|
Identifies the modification of an AWS RDS DB instance or cluster to remove the deletionProtection feature. Deletion protection is enabled automatically for instances set up through the console and can be used to protect them from unintentional deletion activity. If disabled an instance or cluster can be deleted, destroying sensitive or critical information. Adversaries with the proper permissions can take advantage of this to set up future deletion events against a compromised environment. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Resources: Investigation Guide], [Use Case: Threat Detection], [Tactic: Impact] |
None |
2 |
|
Identifies the modification of the master password for an AWS RDS DB instance or cluster. DB instances may contain sensitive data that can be abused if accessed by unauthorized actors. Amazon RDS API operations never return the password, so this operation provides a means to regain access if the password is lost. Adversaries with the proper permissions can take advantage of this to evade defenses and gain unauthorized access to a DB instance or cluster to support persistence mechanisms or privilege escalation. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Resources: Investigation Guide], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Defense Evasion] |
None |
2 |
|
Identifies when an AWS RDS DB Snapshot is created. This can be used to evade defenses by allowing an attacker to bypass access controls or cover their tracks by reverting an instance to a previous state. This is a [building block rule](https://www.elastic.co/guide/en/security/current/building-block-rule.html) and does not generate alerts on its own. It is meant to be used for correlation with other rules to detect suspicious activity. To generate alerts, create a rule that uses this signal as a building block. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Defense Evasion], [Rule Type: BBR] |
None |
1 |
|
Identifies an AWS RDS DB snapshot being shared with another AWS account. DB snapshots contain a full backup of an entire DB instance including sensitive data that can be abused if shared with unauthorized accounts or made public. Adversaries may use snapshots to restore a DB Instance in an environment they control as a means of data exfiltration. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Resources: Investigation Guide], [Use Case: Threat Detection], [Tactic: Exfiltration] |
None |
2 |
|
Identifies the creation of an Amazon Relational Database Service (RDS) Aurora database instance. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Persistence] |
None |
206 |
|
Identifies that an Amazon Relational Database Service (RDS) cluster or instance has been stopped. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Impact] |
None |
206 |
|
Identifies the creation of an Amazon Relational Database Service (RDS) Security group. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Tactic: Persistence] |
None |
206 |
|
Identifies the deletion of an Amazon Relational Database Service (RDS) Security group. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Tactic: Impact] |
None |
206 |
|
Identifies the deletion of an AWS RDS DB snapshot. Snapshots contain a full backup of an entire DB instance. Unauthorized deletion of snapshots can make it impossible to recover critical or sensitive data. This rule detects deleted snapshots and instances modified so that backupRetentionPeriod is set to 0 which disables automated backups and is functionally similar to deleting the system snapshot. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Impact] |
None |
2 |
|
Identifies the export of an Amazon Relational Database Service (RDS) Aurora database snapshot. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Exfiltration] |
None |
206 |
|
Identifies the creation of an Amazon Redshift cluster. Unexpected creation of this cluster by a non-administrative user may indicate a permission or role issue with current users. If unexpected, the resource may not properly be configured and could introduce security vulnerabilities. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Redshift], [Use Case: Asset Visibility], [Tactic: Persistence] |
None |
206 |
|
Identifies attempts to login to AWS as the root user without using multi-factor authentication (MFA). Amazon AWS best practices indicate that the root user should be protected by MFA. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Privilege Escalation] |
None |
209 |
|
Identifies when a transfer lock was removed from a Route 53 domain. It is recommended to refrain from performing this action unless intending to transfer the domain to a different registrar. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Asset Visibility], [Tactic: Persistence] |
None |
206 |
|
Identifies when a request has been made to transfer a Route 53 domain to another AWS account. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Asset Visibility], [Tactic: Persistence] |
None |
206 |
|
Identifies when an AWS Route Table has been created. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Network Security Monitoring], [Tactic: Persistence] |
None |
207 |
|
Identifies when an AWS Route Table has been modified or deleted. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Network Security Monitoring], [Tactic: Persistence] |
None |
207 |
|
Identifies when a Route53 private hosted zone has been associated with VPC. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Asset Visibility], [Tactic: Persistence] |
None |
206 |
|
Identifies the deletion of various Amazon Simple Storage Service (S3) bucket configuration components. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Defense Evasion] |
None |
207 |
|
Identifies a high number of failed S3 operations from a single source and account (or anonymous account) within a short timeframe. This activity can be indicative of attempting to cause an increase in billing to an account for excessive random operations, cause resource exhaustion, or enumerating bucket names for discovery. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS S3], [Resources: Investigation Guide], [Use Case: Log Auditing], [Tactic: Impact] |
8.13.0 |
4 |
|
Identifies an expiration lifecycle configuration added to an S3 bucket. Lifecycle configurations can be used to manage objects in a bucket, including setting expiration policies. This rule detects when a lifecycle configuration is added to an S3 bucket, which could indicate that objects in the bucket will be automatically deleted after a specified period of time. This could be used to evade detection by deleting objects that contain evidence of malicious activity. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon S3], [Use Case: Asset Visibility], [Tactic: Defense Evasion] |
None |
2 |
|
Identifies an AWS S3 bucket policy change to share permissions with an external account. Adversaries may attempt to backdoor an S3 bucket by sharing it with an external account. This can be used to exfiltrate data or to provide access to other adversaries. This rule identifies changes to a bucket policy via the |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS S3], [Use Case: Threat Detection], [Tactic: Exfiltration] |
None |
2 |
|
Identifies when the |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS S3], [Resources: Investigation Guide], [Use Case: Threat Detection], [Tactic: Exfiltration] |
None |
1 |
|
Identifies when server access logging is disabled for an Amazon S3 bucket. Server access logs provide a detailed record of requests made to an S3 bucket. When server access logging is disabled for a bucket, it could indicate an adversary’s attempt to impair defenses by disabling logs that contain evidence of malicious activity. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon S3], [Use Case: Asset Visibility], [Tactic: Defense Evasion] |
None |
1 |
|
Identifies |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS S3], [Data Source: AWS KMS], [Use Case: Threat Detection], [Tactic: Impact] |
8.13.0 |
2 |
|
Identifies when object versioning is suspended for an Amazon S3 bucket. Object versioning allows for multiple versions of an object to exist in the same bucket. This allows for easy recovery of deleted or overwritten objects. When object versioning is suspended for a bucket, it could indicate an adversary’s attempt to inhibit system recovery following malicious activity. Additionally, when versioning is suspended, buckets can then be deleted. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS S3], [Use Case: Threat Detection], [Tactic: Impact] |
None |
2 |
|
Identifies when an SNS topic is subscribed to by an email address of a user who does not typically perform this action. Adversaries may subscribe to an SNS topic to collect sensitive information or exfiltrate data via an external email address. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS SNS], [Resources: Investigation Guide], [Use Case: Threat Detection], [Tactic: Exfiltration] |
None |
1 |
|
Identifies when an AWS Systems Manager (SSM) command document is created by a user who does not typically perform this action. Adversaries may create SSM command documents to execute commands on managed instances, potentially leading to unauthorized access, command and control, data exfiltration and more. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS SNS], [Data Source: AWS Systems Manager], [Resources: Investigation Guide], [Use Case: Threat Detection], [Tactic: Execution] |
None |
1 |
|
Detects the execution of commands or scripts on EC2 instances using AWS Systems Manager (SSM), such as |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS SSM], [Use Case: Log Auditing], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide] |
None |
210 |
|
Identifies the use of the AWS Systems Manager (SSM) |
[Domain: Endpoint], [Domain: Cloud], [OS: Linux], [OS: macOS], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
Identifies when a user has assumed a role using a new MFA device. Users can assume a role to obtain temporary credentials and access AWS resources using the AssumeRole API of AWS Security Token Service (STS). While a new MFA device is not always indicative of malicious behavior it should be verified as adversaries can use this technique for persistence and privilege escalation. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation], [Tactic: Persistence], [Tactic: Lateral Movement] |
None |
1 |
|
Identifies when the STS |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Resources: Investigation Guide], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |
None |
1 |
|
An adversary with access to a set of compromised credentials may attempt to verify that the credentials are valid and determine what account they are using. This rule looks for the first time an identity has called the STS |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Tactic: Discovery], [Resources: Investigation Guide] |
None |
3 |
|
Identifies the suspicious use of GetSessionToken. Tokens could be created and used by attackers to move laterally and escalate privileges. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |
None |
206 |
|
Identifies when a service has assumed a role in AWS Security Token Service (STS). Services can assume a role to obtain temporary credentials and access AWS resources. Adversaries can use this technique for credential access and privilege escalation. This is a [New Terms](https://www.elastic.co/guide/en/security/current/rules-ui-create.html#create-new-terms-rule) rule that identifies when a service assumes a role in AWS Security Token Service (STS) to obtain temporary credentials and access AWS resources. While often legitimate, adversaries may use this technique for unauthorized access, privilege escalation, or lateral movement within an AWS environment. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Resources: Investigation Guide], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |
None |
209 |
|
Identifies when a user or role has assumed a role in AWS Security Token Service (STS). Users can assume a role to obtain temporary credentials and access AWS resources. Adversaries can use this technique for credential access and privilege escalation. This is a [New Terms](https://www.elastic.co/guide/en/security/current/rules-ui-create.html#create-new-terms-rule) rule that identifies when a service assumes a role in AWS Security Token Service (STS) to obtain temporary credentials and access AWS resources. While often legitimate, adversaries may use this technique for unauthorized access, privilege escalation, or lateral movement within an AWS environment. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Resources: Investigation Guide], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |
None |
1 |
|
Identifies role chaining activity. Role chaining is when you use one assumed role to assume a second role through the AWS CLI or API. While this a recognized functionality in AWS, role chaining can be abused for privilege escalation if the subsequent assumed role provides additional privileges. Role chaining can also be used as a persistence mechanism as each AssumeRole action results in a refreshed session token with a 1 hour maximum duration. This rule looks for role chaining activity happening within a single account, to eliminate false positives produced by common cross-account behavior. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Lateral Movement] |
None |
1 |
|
Identifies when a single AWS resource is making |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Service Quotas], [Use Case: Threat Detection], [Tactic: Discovery] |
None |
2 |
|
Identifies when a federated user logs into the AWS Management Console without using multi-factor authentication (MFA). Federated users are typically given temporary credentials to access AWS services. If a federated user logs into the AWS Management Console without using MFA, it may indicate a security risk, as MFA adds an additional layer of security to the authentication process. This could also indicate the abuse of STS tokens to bypass MFA requirements. |
[Domain: Cloud], [Data Source: Amazon Web Services], [Data Source: AWS], [Data Source: AWS Sign-In], [Use Case: Threat Detection], [Tactic: Initial Access] |
8.13.0 |
2 |
|
AWS Systems Manager SecureString Parameter Request with Decryption Flag |
Detects the first occurrence of a user identity accessing AWS Systems Manager (SSM) SecureString parameters using the GetParameter or GetParameters API actions with credentials in the request parameters. This could indicate that the user is accessing sensitive information. This rule detects when a user accesses a SecureString parameter with the |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Systems Manager], [Tactic: Credential Access], [Resources: Investigation Guide] |
None |
2 |
Identifies the deletion of one or more flow logs in AWS Elastic Compute Cloud (EC2). An adversary may delete flow logs in an attempt to evade defenses. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |
None |
209 |
|
Identifies the deletion of a specified AWS Web Application Firewall (WAF) access control list. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies the deletion of a specified AWS Web Application Firewall (WAF) rule or rule group. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies the creation of a Process ID (PID), lock or reboot file created in temporary file storage paradigm (tmpfs) directory /var/run. On Linux, the PID files typically hold the process ID to track previous copies running and manage other tasks. Certain Linux malware use the /var/run directory for holding data, executables and other tasks, disguising itself or these files as legitimate PID files. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: BPFDoor], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
214 |
|
Specially crafted DNS requests can manipulate a known overflow vulnerability in some Windows DNS servers, resulting in Remote Code Execution (RCE) or a Denial of Service (DoS) from crashing the service. |
[Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Use Case: Vulnerability] |
None |
105 |
|
This rule detects network events that may indicate the use of Telnet traffic. Telnet is commonly used by system administrators to remotely control older or embedded systems using the command line shell. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. As a plain-text protocol, it may also expose usernames and passwords to anyone capable of observing the traffic. |
[Domain: Endpoint], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Lateral Movement], [Tactic: Initial Access], [Data Source: PAN-OS] |
None |
106 |
|
This rule detects Linux Access Control List (ACL) modification via the setfacl command. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
2 |
|
Adversaries may collect the keychain storage data from a system to acquire credentials. Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features such as WiFi passwords, websites, secure notes and certificates. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
207 |
|
Identify access to sensitive Active Directory object attributes that contains credentials and decryption keys such as unixUserPassword, ms-PKI-AccountCredentials and msPKI-CredentialRoamingTokens. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Data Source: System] |
None |
12 |
|
Identifies commands containing references to Outlook data files extensions, which can potentially indicate the search, access, or modification of these files. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Sysmon], [Data Source: Elastic Endgame], [Data Source: System] |
None |
5 |
|
Detects the creation and modification of an account with the "Don’t Expire Password" option Enabled. Attackers can abuse this misconfiguration to persist in the domain and maintain long-term access using compromised accounts with this property. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
111 |
|
Identifies when the SYSTEM account uses an account discovery utility. This could be a sign of discovery activity after an adversary has achieved privilege escalation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
111 |
|
Identifies an attempt to reset a potentially privileged account password remotely. Adversaries may manipulate account passwords to maintain access or evade password duration policies and preserve compromised credentials. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Impact], [Data Source: System] |
None |
116 |
|
Adversaries may use built-in applications to get a listing of local system or domain accounts and groups. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
Active Directory Forced Authentication from Linux Host - SMB Named Pipes |
Identifies a potential forced authentication using related SMB named pipes. Attackers may attempt to force targets to authenticate to a host controlled by them to capture hashes or enable relay attacks. |
[Domain: Endpoint], [OS: Windows], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Active Directory], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
3 |
Identifies a user being added to an active directory group by the SYSTEM (S-1-5-18) user. This behavior can indicate that the attacker has achieved SYSTEM privileges in a domain controller, which attackers can obtain by exploiting vulnerabilities or abusing default group privileges (e.g., Server Operators), and is attempting to pivot to a domain account. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Data Source: System] |
None |
2 |
|
This rule detects the Active Directory query tool, AdFind.exe. AdFind has legitimate purposes, but it is frequently leveraged by threat actors to perform post-exploitation Active Directory reconnaissance. The AdFind tool has been observed in Trickbot, Ryuk, Maze, and FIN6 campaigns. For Winlogbeat, this rule requires Sysmon. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Adversaries can add the hidden attribute to files to hide them from the user in an attempt to evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Detects modifications in the AdminSDHolder object. Attackers can abuse the SDProp process to implement a persistent backdoor in Active Directory. SDProp compares the permissions on protected objects with those defined on the AdminSDHolder object. If the permissions on any of the protected accounts and groups do not match, the permissions on the protected accounts and groups are reset to match those of the domain’s AdminSDHolder object, regaining their Administrative Privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Data Source: System] |
None |
110 |
|
Identifies a modification on the dsHeuristics attribute on the bit that holds the configuration of groups excluded from the SDProp process. The SDProp compares the permissions on protected objects with those defined on the AdminSDHolder object. If the permissions on any of the protected accounts and groups do not match, the permissions on the protected accounts and groups are reset to match those of the domain’s AdminSDHolder object, meaning that groups excluded will remain unchanged. Attackers can abuse this misconfiguration to maintain long-term access to privileged accounts in these groups. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
112 |
|
Detects when an administrator role is assigned to an Okta group. An adversary may attempt to assign administrator privileges to an Okta group in order to assign additional permissions to compromised user accounts and maintain access to their target organization. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Persistence] |
None |
208 |
|
Identifies when an administrator role is assigned to an Okta user. An adversary may attempt to assign an administrator role to an Okta user in order to assign additional permissions to a user account and maintain access to their target’s environment. |
[Data Source: Okta], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
208 |
|
Detects writing executable files that will be automatically launched by Adobe on launch. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
314 |
|
Elastic Endgame detected an Adversary Behavior. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame] |
None |
104 |
|
Detects events that have a mismatch on the expected event agent ID. The status "agent_id_mismatch/mismatch" occurs when the expected agent ID associated with the API key does not match the actual agent ID in an event. This could indicate attempts to spoof events in order to masquerade actual activity to evade detection. |
[Use Case: Threat Detection], [Tactic: Defense Evasion] |
None |
102 |
|
Detects when multiple hosts are using the same agent ID. This could occur in the event of an agent being taken over and used to inject illegitimate documents into an instance as an attempt to spoof events in order to masquerade actual activity to evade detection. |
[Use Case: Threat Detection], [Tactic: Defense Evasion] |
None |
102 |
|
Alternate Data Stream Creation/Execution at Volume Root Directory |
Identifies the creation of an Alternate Data Stream (ADS) at a volume root directory, which can indicate the attempt to hide tools and malware, as ADSs created in this directory are not displayed by system utilities. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Elastic Endgame] |
8.13.0 |
101 |
Looks for compiler activity by a user context which does not normally run compilers. This can be the result of ad-hoc software changes or unauthorized software deployment. This can also be due to local privilege elevation via locally run exploits or malware activity. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Resource Development] |
None |
104 |
|
Searches for rare processes running on multiple Linux hosts in an entire fleet or network. This reduces the detection of false positives since automated maintenance processes usually only run occasionally on a single machine but are common to all or many hosts in a fleet. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
105 |
|
Searches for rare processes running on multiple hosts in an entire fleet or network. This reduces the detection of false positives since automated maintenance processes usually only run occasionally on a single machine but are common to all or many hosts in a fleet. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Tactic: Execution] |
None |
108 |
|
Identifies unusual parent-child process relationships that can indicate malware execution or persistence mechanisms. Malicious scripts often call on other applications and processes as part of their exploit payload. For example, when a malicious Office document runs scripts as part of an exploit payload, Excel or Word may start a script interpreter process, which, in turn, runs a script that downloads and executes malware. Another common scenario is Outlook running an unusual process when malware is downloaded in an email. Monitoring and identifying anomalous process relationships is a method of detecting new and emerging malware that is not yet recognized by anti-virus scanners. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
108 |
|
Detects execution via the Apple script interpreter (osascript) followed by a network connection from the same process within a short time period. Adversaries may use malicious scripts for execution and command and control. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies execution of the Apple script interpreter (osascript) without a password prompt and with administrator privileges. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
207 |
|
Detects when a Google marketplace application is added to the Google Workspace domain. An adversary may add a malicious application to an organization’s Google Workspace domain in order to maintain a presence in their target’s organization and steal data. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
206 |
|
Google Workspace administrators may be aware of malicious applications within the Google marketplace and block these applications for user security purposes. An adversary, with administrative privileges, may remove this application from the explicit block list to allow distribution of the application amongst users. This may also indicate the unauthorized use of an application that had been previously blocked before by a user with admin privileges. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Resources: Investigation Guide], [Tactic: Defense Evasion] |
None |
107 |
|
Identifies the creation of an archive file with an unusual extension. Attackers may attempt to evade detection by masquerading files using the file extension values used by image, audio, or document file types. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
2 |
|
This rule monitors for at jobs being created or renamed. Linux at jobs are scheduled tasks that can be leveraged by system administrators to set up scheduled tasks, but may be abused by malicious actors for persistence, privilege escalation and command execution. By creating or modifying cron job configurations, attackers can execute malicious commands or scripts at predefined intervals, ensuring their continued presence and enabling unauthorized activities. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies use of at.exe to interact with the task scheduler on remote hosts. Remote task creations, modifications or execution could be indicative of adversary lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame], [Data Source: System] |
None |
5 |
|
Monitors for the deletion of the kernel ring buffer events through dmesg. Attackers may clear kernel ring buffer events to evade detection after installing a Linux kernel module (LKM). |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
5 |
|
Detects attempts to create an Okta API token. An adversary may create an Okta API token to maintain access to an organization’s network while they work to achieve their objectives. An attacker may abuse an API token to execute techniques such as creating user accounts or disabling security rules or policies. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Persistence] |
None |
208 |
|
Detects attempts to deactivate an Okta application. An adversary may attempt to modify, deactivate, or delete an Okta application in order to weaken an organization’s security controls or disrupt their business operations. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Impact] |
None |
209 |
|
Detects attempts to deactivate an Okta network zone. Okta network zones can be configured to limit or restrict access to a network based on IP addresses or geolocations. An adversary may attempt to modify, delete, or deactivate an Okta network zone in order to remove or weaken an organization’s security controls. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |
None |
209 |
|
Detects attempts to deactivate an Okta policy. An adversary may attempt to deactivate an Okta policy in order to weaken an organization’s security controls. For example, an adversary may attempt to deactivate an Okta multi-factor authentication (MFA) policy in order to weaken the authentication requirements for user accounts. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Defense Evasion] |
None |
209 |
|
Detects attempts to deactivate a rule within an Okta policy. An adversary may attempt to deactivate a rule within an Okta policy in order to remove or weaken an organization’s security controls. |
[Use Case: Identity and Access Audit], [Tactic: Defense Evasion], [Data Source: Okta] |
None |
210 |
|
Detects attempts to delete an Okta application. An adversary may attempt to modify, deactivate, or delete an Okta application in order to weaken an organization’s security controls or disrupt their business operations. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Impact] |
None |
208 |
|
Detects attempts to delete an Okta network zone. Okta network zones can be configured to limit or restrict access to a network based on IP addresses or geolocations. An adversary may attempt to modify, delete, or deactivate an Okta network zone in order to remove or weaken an organization’s security controls. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |
None |
209 |
|
Detects attempts to delete an Okta policy. An adversary may attempt to delete an Okta policy in order to weaken an organization’s security controls. For example, an adversary may attempt to delete an Okta multi-factor authentication (MFA) policy in order to weaken the authentication requirements for user accounts. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Defense Evasion] |
None |
209 |
|
Detects attempts to delete a rule within an Okta policy. An adversary may attempt to delete an Okta policy rule in order to weaken an organization’s security controls. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Defense Evasion] |
None |
209 |
|
Adversaries may attempt to disable the Auditd service to evade detection. Auditd is a Linux service that provides system auditing and logging. Disabling the Auditd service can prevent the system from logging important security events, which can be used to detect malicious activity. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
1 |
|
Detects attempts to disable Gatekeeper on macOS. Gatekeeper is a security feature that’s designed to ensure that only trusted software is run. Adversaries may attempt to disable Gatekeeper before executing malicious code. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
106 |
|
Adversaries may attempt to disable the iptables or firewall service in an attempt to affect how a host is allowed to receive or send network traffic. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
9 |
|
Adversaries may attempt to disable the syslog service in an attempt to an attempt to disrupt event logging and evade detection by security controls. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
110 |
|
Identifies attempts to enable the root account using the dsenableroot command. This command may be abused by adversaries for persistence, as the root account is disabled by default. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
106 |
|
Detects the execution of the VScode portable binary with the tunnel command line option indicating an attempt to establish a remote tunnel session to Github or a remote VScode instance. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
8.13.0 |
3 |
|
Detects attempts to install or use Kali Linux via Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
108 |
|
Adversaries may install a root certificate on a compromised system to avoid warnings when connecting to their command and control servers. Root certificates are used in public key cryptography to identify a root certificate authority (CA). When a root certificate is installed, the system or application will trust certificates in the root’s chain of trust that have been signed by the root certificate. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
106 |
|
Detects attempts to modify an Okta application. An adversary may attempt to modify, deactivate, or delete an Okta application in order to weaken an organization’s security controls or disrupt their business operations. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Impact] |
None |
208 |
|
Detects attempts to modify an Okta network zone. Okta network zones can be configured to limit or restrict access to a network based on IP addresses or geolocations. An adversary may attempt to modify, delete, or deactivate an Okta network zone in order to remove or weaken an organization’s security controls. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |
None |
209 |
|
Detects attempts to modify an Okta policy. An adversary may attempt to modify an Okta policy in order to weaken an organization’s security controls. For example, an adversary may attempt to modify an Okta multi-factor authentication (MFA) policy in order to weaken the authentication requirements for user accounts. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Defense Evasion] |
None |
209 |
|
Detects attempts to modify a rule within an Okta policy. An adversary may attempt to modify an Okta policy rule in order to weaken an organization’s security controls. |
[Use Case: Identity and Access Audit], [Tactic: Defense Evasion], [Data Source: Okta] |
None |
210 |
|
Identifies the execution of macOS built-in commands to mount a Server Message Block (SMB) network share. Adversaries may use valid accounts to interact with a remote network share using SMB. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |
None |
107 |
|
Detects attempts to reset an Okta user’s enrolled multi-factor authentication (MFA) factors. An adversary may attempt to reset the MFA factors for an Okta user’s account in order to register new MFA factors and abuse the account to blend in with normal activity in the victim’s environment. |
[Tactic: Persistence], [Use Case: Identity and Access Audit], [Data Source: Okta] |
None |
209 |
|
Identifies discovery request |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon EC2], [Use Case: Log Auditing], [Tactic: Discovery], [Rule Type: BBR] |
None |
2 |
|
Identifies attempts to revoke an Okta API token. An adversary may attempt to revoke or delete an Okta API token to disrupt an organization’s business operations. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Impact] |
None |
209 |
|
Attempt to Unload Elastic Endpoint Security Kernel Extension |
Identifies attempts to unload the Elastic Endpoint Security kernel extension via the kextunload command. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
106 |
Detects attempts to bypass Okta multi-factor authentication (MFA). An adversary may attempt to bypass the Okta MFA policies configured for an organization in order to obtain unauthorized access to an application. |
[Data Source: Okta], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |
None |
210 |
|
Attackers may try to access private keys, e.g. ssh, in order to gain further authenticated access to the environment. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Sysmon], [Data Source: Elastic Endgame], [Data Source: System] |
None |
6 |
|
Identifies potential brute-force attempts against Microsoft 365 user accounts by detecting a high number of failed login attempts or login sources within a 30-minute window. Attackers may attempt to brute force user accounts to gain unauthorized access to Microsoft 365 services. |
[Domain: Cloud], [Domain: SaaS], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Tactic: Credential Access] |
8.13.0 |
311 |
|
Identifies when an Okta user account is locked out 3 times within a 3 hour window. An adversary may attempt a brute force or password spraying attack to obtain unauthorized access to user accounts. The default Okta authentication policy ensures that a user account is locked out after 10 failed authentication attempts. |
[Use Case: Identity and Access Audit], [Tactic: Credential Access], [Data Source: Okta] |
None |
211 |
|
This rule detects successful authentications via PAM grantors that are not commonly used. This could indicate an attacker is attempting to escalate privileges or maintain persistence on the system by modifying the default PAM configuration. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Data Source: Auditd Manager] |
None |
1 |
|
Authorization plugins are used to extend the authorization services API and implement mechanisms that are not natively supported by the OS, such as multi-factor authentication with third party software. Adversaries may abuse this feature to persist and/or collect clear text credentials as they traverse the registered plugins during user logon. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
107 |
|
In Azure Active Directory (Azure AD), permissions to manage resources are assigned using roles. The Global Administrator is a role that enables users to have access to all administrative features in Azure AD and services that use Azure AD identities like the Microsoft 365 Defender portal, the Microsoft 365 compliance center, Exchange, SharePoint Online, and Skype for Business Online. Attackers can add users as Global Administrators to maintain access and manage all subscriptions and their settings and resources. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
102 |
|
Identifies high risk Azure Active Directory (AD) sign-ins by leveraging Microsoft’s Identity Protection machine learning and heuristics. Identity Protection categorizes risk into three tiers: low, medium, and high. While Microsoft does not provide specific details about how risk is calculated, each level brings higher confidence that the user or sign-in is compromised. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |
None |
105 |
|
Identifies high risk Azure Active Directory (AD) sign-ins by leveraging Microsoft Identity Protection machine learning and heuristics. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |
None |
105 |
|
Identifies a sign-in using the Azure Active Directory PowerShell module. PowerShell for Azure Active Directory allows for managing settings from the command line, which is intended for users who are members of an admin role. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |
None |
105 |
|
Identifies the creation of suppression rules in Azure. Suppression rules are a mechanism used to suppress alerts previously identified as false positives or too noisy to be in production. This mechanism can be abused or mistakenly configured, resulting in defense evasions and loss of security visibility. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
102 |
|
Identifies when a new credential is added to an application in Azure. An application may use a certificate or secret string to prove its identity when requesting a token. Multiple certificates and secrets can be added for an application and an adversary may abuse this by creating an additional authentication method to evade defenses or persist in an environment. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |
None |
102 |
|
Identifies when an Azure Automation account is created. Azure Automation accounts can be used to automate management tasks and orchestrate actions across systems. An adversary may create an Automation account in order to maintain persistence in their target’s environment. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
102 |
|
Identifies when an Azure Automation runbook is created or modified. An adversary may create or modify an Azure Automation runbook to execute malicious code and maintain persistence in their target’s environment. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |
None |
102 |
|
Identifies when an Azure Automation runbook is deleted. An adversary may delete an Azure Automation runbook in order to disrupt their target’s automated business operations or to remove a malicious runbook for defense evasion. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
102 |
|
Identifies when an Azure Automation webhook is created. Azure Automation runbooks can be configured to execute via a webhook. A webhook uses a custom URL passed to Azure Automation along with a data payload specific to the runbook. An adversary may create a webhook in order to trigger a runbook that contains malicious code. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |
None |
102 |
|
Identifies changes to container access levels in Azure. Anonymous public read access to containers and blobs in Azure is a way to share data broadly, but can present a security risk if access to sensitive data is not managed judiciously. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Asset Visibility], [Tactic: Discovery] |
None |
102 |
|
Identifies when the Azure role-based access control (Azure RBAC) permissions are modified for an Azure Blob. An adversary may modify the permissions on a blob to weaken their target’s security controls or an administrator may inadvertently modify the permissions, which could lead to data exposure or loss. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
103 |
|
Identifies command execution on a virtual machine (VM) in Azure. A Virtual Machine Contributor role lets you manage virtual machines, but not access them, nor access the virtual network or storage account they’re connected to. However, commands can be run via PowerShell on the VM, which execute as System. Other roles, such as certain Administrator roles may be able to execute commands on a VM as well. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Execution] |
None |
102 |
|
Identifies when an Azure Conditional Access policy is modified. Azure Conditional Access policies control access to resources via if-then statements. For example, if a user wants to access a resource, then they must complete an action such as using multi-factor authentication to access it. An adversary may modify a Conditional Access policy in order to weaken their target’s security controls. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |
None |
102 |
|
Identifies the deletion of diagnostic settings in Azure, which send platform logs and metrics to different destinations. An adversary may delete diagnostic settings in an attempt to evade defenses. |
[Domain: Cloud], [Data Source: Azure], [Tactic: Defense Evasion] |
None |
102 |
|
Azure Entra Sign-in Brute Force Microsoft 365 Accounts by Repeat Source |
Identifies potential brute-force attempts against Microsoft 365 user accounts by detecting a high number of failed interactive or non-interactive login attempts within a 30-minute window from a single source. Attackers may attempt to brute force user accounts to gain unauthorized access to Microsoft 365 services via different services such as Exchange, SharePoint, or Teams. |
[Domain: Cloud], [Domain: SaaS], [Data Source: Azure], [Data Source: Entra ID], [Data Source: Entra ID Sign-in], [Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Tactic: Credential Access] |
8.13.0 |
2 |
Azure Entra Sign-in Brute Force against Microsoft 365 Accounts |
Identifies potential brute-force attempts against Microsoft 365 user accounts by detecting a high number of failed interactive or non-interactive login attempts within a 30-minute window. Attackers may attempt to brute force user accounts to gain unauthorized access to Microsoft 365 services via different services such as Exchange, SharePoint, or Teams. |
[Domain: Cloud], [Domain: SaaS], [Data Source: Azure], [Data Source: Entra ID], [Data Source: Entra ID Sign-in], [Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Tactic: Credential Access] |
8.13.0 |
2 |
Identifies when an Event Hub Authorization Rule is created or updated in Azure. An authorization rule is associated with specific rights, and carries a pair of cryptographic keys. When you create an Event Hubs namespace, a policy rule named RootManageSharedAccessKey is created for the namespace. This has manage permissions for the entire namespace and it’s recommended that you treat this rule like an administrative root account and don’t use it in your application. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Collection] |
None |
103 |
|
Identifies an Event Hub deletion in Azure. An Event Hub is an event processing service that ingests and processes large volumes of events and data. An adversary may delete an Event Hub in an attempt to evade detection. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Defense Evasion] |
None |
102 |
|
Identifies an invitation to an external user in Azure Active Directory (AD). Azure AD is extended to include collaboration, allowing you to invite people from outside your organization to be guest users in your cloud account. Unless there is a business need to provision guest access, it is best practice avoid creating guest users. Guest users could potentially be overlooked indefinitely leading to a potential vulnerability. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |
None |
102 |
|
Identifies the deletion of a firewall policy in Azure. An adversary may delete a firewall policy in an attempt to evade defenses and/or to eliminate barriers to their objective. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |
None |
102 |
|
Azure Frontdoor Web Application Firewall (WAF) Policy Deleted |
Identifies the deletion of a Frontdoor Web Application Firewall (WAF) Policy in Azure. An adversary may delete a Frontdoor Web Application Firewall (WAF) Policy in an attempt to evade defenses and/or to eliminate barriers to their objective. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |
None |
102 |
Identifies potential full network packet capture in Azure. Packet Capture is an Azure Network Watcher feature that can be used to inspect network traffic. This feature can potentially be abused to read sensitive data from unencrypted internal traffic. |
[Domain: Cloud], [Data Source: Azure], [Tactic: Credential Access] |
None |
103 |
|
Identifies an Azure Active Directory (AD) Global Administrator role addition to a Privileged Identity Management (PIM) user account. PIM is a service that enables you to manage, control, and monitor access to important resources in an organization. Users who are assigned to the Global administrator role can read and modify any administrative setting in your Azure AD organization. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
102 |
|
Identifies modifications to a Key Vault in Azure. The Key Vault is a service that safeguards encryption keys and secrets like certificates, connection strings, and passwords. Because this data is sensitive and business critical, access to key vaults should be secured to allow only authorized applications and users. |
[Domain: Cloud], [Data Source: Azure], [Tactic: Credential Access] |
None |
103 |
|
Identifies when events are deleted in Azure Kubernetes. Kubernetes events are objects that log any state changes. Example events are a container creation, an image pull, or a pod scheduling on a node. An adversary may delete events in Azure Kubernetes in an attempt to evade detection. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Defense Evasion] |
None |
102 |
|
Identifies the deletion of Azure Kubernetes Pods. Adversaries may delete a Kubernetes pod to disrupt the normal behavior of the environment. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Asset Visibility], [Tactic: Impact] |
None |
102 |
|
Identifies the creation of role binding or cluster role bindings. You can assign these roles to Kubernetes subjects (users, groups, or service accounts) with role bindings and cluster role bindings. An adversary who has permissions to create bindings and cluster-bindings in the cluster can create a binding to the cluster-admin ClusterRole or to other high privileges roles. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |
None |
102 |
|
Identifies the deletion of a Network Watcher in Azure. Network Watchers are used to monitor, diagnose, view metrics, and enable or disable logs for resources in an Azure virtual network. An adversary may delete a Network Watcher in an attempt to evade defenses. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |
None |
102 |
|
Azure Active Directory (AD) Privileged Identity Management (PIM) is a service that enables you to manage, control, and monitor access to important resources in an organization. PIM can be used to manage the built-in Azure resource roles such as Global Administrator and Application Administrator. An adversary may add a user to a PIM role in order to maintain persistence in their target’s environment or modify a PIM role to weaken their target’s security controls. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |
None |
105 |
|
Identifies the deletion of a resource group in Azure, which includes all resources within the group. Deletion is permanent and irreversible. An adversary may delete a resource group in an attempt to evade defenses or intentionally destroy data. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Impact] |
None |
102 |
|
Identifies when a new service principal is added in Azure. An application, hosted service, or automated tool that accesses or modifies resources needs an identity created. This identity is known as a service principal. For security reasons, it’s always recommended to use service principals with automated tools rather than allowing them to log in with a user identity. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Defense Evasion] |
None |
105 |
|
Identifies when new Service Principal credentials have been added in Azure. In most organizations, credentials will be added to service principals infrequently. Hijacking an application (by adding a rogue secret or certificate) with granted permissions will allow the attacker to access data that is normally protected by MFA requirements. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Impact] |
None |
102 |
|
Identifies a rotation to storage account access keys in Azure. Regenerating access keys can affect any applications or Azure services that are dependent on the storage account key. Adversaries may regenerate a key as a means of acquiring credentials to access systems and resources. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |
None |
102 |
|
Identifies when a virtual network device is modified or deleted. This can be a network virtual appliance, virtual hub, or virtual router. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Impact] |
None |
102 |
|
Detects when the tc (transmission control) binary is utilized to set a BPF (Berkeley Packet Filter) on a network interface. Tc is used to configure Traffic Control in the Linux kernel. It can shape, schedule, police and drop traffic. A threat actor can utilize tc to set a bpf filter on an interface for the purpose of manipulating the incoming traffic. This technique is not at all common and should indicate abnormal, suspicious or malicious activity. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: TripleCross], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
108 |
|
Adversaries may encode/decode data in an attempt to evade detection by host- or network-based security controls. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
110 |
|
Both ~/.bash_profile and ~/.bashrc are files containing shell commands that are run when Bash is invoked. These files are executed in a user’s context, either interactively or non-interactively, when a user logs in so that their environment is set correctly. Adversaries may abuse this to establish persistence by executing malicious content triggered by a user’s shell. |
[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
104 |
|
Attackers may abuse cmd.exe commands to reassemble binary fragments into a malicious payload. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Sysmon], [Data Source: Elastic Endgame], [Data Source: System] |
None |
6 |
|
Identifies the execution of a binary by root in Linux shared memory directories: (/dev/shm/, /run/shm/, /var/run/, /var/lock/). This activity is to be considered highly abnormal and should be investigated. Threat actors have placed executables used for persistence on high-uptime servers in these directories as system backdoors. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: BPFDoor], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
110 |
|
Windows Background Intelligent Transfer Service (BITS) is a low-bandwidth, asynchronous file transfer mechanism. Adversaries may abuse BITS to persist, download, execute, and even clean up after running malicious code. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Sysmon], [Data Source: Elastic Endgame], [Data Source: System] |
None |
5 |
|
Identifies the install of browser extensions. Malicious browser extensions can be installed via app store downloads masquerading as legitimate extensions, social engineering, or by an adversary that has already compromised a system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: SentinelOne], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
102 |
|
Identifies User Account Control (UAC) bypass via eventvwr.exe. Attackers bypass UAC to stealthily execute code with elevated permissions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: System], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
214 |
|
Identifies instances where a binary is granted the CAP_SYS_ADMIN capability. In Linux, the CAP_SYS_ADMIN capability is a powerful and broad capability that allows a process to perform a range of system administration operations, such as mounting and unmounting filesystems, configuring network interfaces, and accessing hardware devices. Attackers may leverage a misconfiguration for exploitation in order to escalate their privileges to root. The rule identifies previously unknown processes executing with CAP_SYS_ADMIN capabilities through the use of the new terms rule type. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
2 |
|
Detects the use of the chkconfig binary to manually add a service for management by chkconfig. Threat actors may utilize this technique to maintain persistence on a system. When a new service is added, chkconfig ensures that the service has either a start or a kill entry in every runlevel and when the system is rebooted the service file added will run providing long-term persistence. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Lightning Framework], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
113 |
|
Identifies when a user attempts to clear console history. An adversary may clear the command history of a compromised account to conceal the actions undertaken during an intrusion. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies attempts to clear or disable Windows event log stores using Windows wevetutil command. This is often done by attackers in an attempt to evade detection or destroy forensic evidence on a system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
214 |
|
Cobalt Strike is a threat emulation platform commonly modified and used by adversaries to conduct network attack and exploitation campaigns. This rule detects a network activity algorithm leveraged by Cobalt Strike implant beacons for command and control. |
[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |
None |
105 |
|
Identifies attempts to disable/modify the code signing policy through system native utilities. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
109 |
|
Identifies attempts to disable the code signing policy through the registry. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
111 |
|
A suspicious SolarWinds child process (Cmd.exe or Powershell.exe) was detected. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies cmd.exe making a network connection. Adversaries could abuse cmd.exe to download or execute malware from a remote URL. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Identifies command shell activity started via RunDLL32, which is commonly abused by attackers to host malicious code. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies Component Object Model (COM) hijacking via registry modification. Adversaries may establish persistence by executing malicious content triggered by hijacked references to COM objects. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
114 |
|
Identifies the image load of a compression DLL. Adversaries will often compress and encrypt data in preparation for exfiltration. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
3 |
|
Detects when the Console Window Host (conhost.exe) process is spawned by a suspicious parent process, which could be indicative of code injection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Connection to Commonly Abused Free SSL Certificate Providers |
Identifies unusual processes connecting to domains using known free SSL certificates. Adversaries may employ a known encryption algorithm to conceal command and control traffic. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
107 |
Adversaries may implement command and control (C2) communications that use common web services to hide their activity. This attack technique is typically targeted at an organization and uses web services common to the victim network, which allows the adversary to blend into legitimate traffic activity. These popular services are typically targeted since they have most likely been used before compromise, which helps malicious traffic blend in. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
116 |
|
Telnet provides a command line interface for communication with a remote device or server. This rule identifies Telnet network connections to publicly routable IP addresses. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |
None |
107 |
|
Telnet provides a command line interface for communication with a remote device or server. This rule identifies Telnet network connections to non-publicly routable IP addresses. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |
None |
107 |
|
This rule detects when a container management binary is run from inside a container. These binaries are critical components of many containerized environments, and their presence and execution in unauthorized containers could indicate compromise or a misconfiguration. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |
None |
2 |
|
Generates a detection alert each time a Container Workload Protection alert is received. Enabling this rule allows you to immediately begin triaging and investigating these alerts. |
[Data Source: Elastic Defend for Containers], [Domain: Container] |
None |
4 |
|
Identifies unusual instances of Control Panel with suspicious keywords or paths in the process command line value. Adversaries may abuse control.exe to proxy execution of malicious code. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Users can mark specific files as hidden simply by putting a "." as the first character in the file or folder name. Adversaries can use this to their advantage to hide files and folders on the system for persistence and defense evasion. This rule looks for hidden files or folders in common writable directories. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
111 |
|
Identifies the creation of a hidden launch agent or daemon. An adversary may establish persistence by installing a new launch agent or daemon which executes at login. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies the execution of osascript to create a hidden login item. This may indicate an attempt to persist a malicious program while concealing its presence. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
108 |
|
Identifies the creation of a hidden shared object (.so) file. Users can mark specific files as hidden simply by putting a "." as the first character in the file or folder name. Adversaries can use this to their advantage to hide files and folders on the system for persistence and defense evasion. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
110 |
|
Identifies activity related to loading kernel modules on Linux via creation of new ko files in the LKM directory. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
3 |
|
Identifies the suspicious creation of SettingContents-ms files, which have been used in attacks to achieve code execution while evading defenses. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Sysmon], [Data Source: Elastic Endgame] |
None |
6 |
|
Active Directory Integrated DNS (ADIDNS) is one of the core components of AD DS, leveraging AD’s access control and replication to maintain domain consistency. It stores DNS zones as AD objects, a feature that, while robust, introduces some security issues because of the default permission (Any authenticated users) to create DNS-named records. Attackers can perform Dynamic Spoofing attacks, where they monitor LLMNR/NBT-NS requests and create DNS-named records to target systems that are requested from multiple systems. They can also create specific records to target specific services, such as wpad, for spoofing attacks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
3 |
|
Identifies the creation of a hidden local user account by appending the dollar sign to the account name. This is sometimes done by attackers to increase access to a system and avoid appearing in the results of accounts listing using the net users command. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies the creation or modification of Domain Backup private keys. Adversaries may extract the Data Protection API (DPAPI) domain backup key from a Domain Controller (DC) to be able to decrypt any domain user master key file. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
311 |
|
Creation or Modification of Pluggable Authentication Module or Configuration |
This rule monitors for the creation or modification of Pluggable Authentication Module (PAM) shared object files or configuration files. Attackers may create or modify these files to maintain persistence on a compromised system, or harvest account credentials. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
2 |
Identifies the creation or modification of a local trusted root certificate in Windows. The install of a malicious root certificate would allow an attacker the ability to masquerade malicious files as valid signed components from any entity (for example, Microsoft). It could also allow an attacker to decrypt SSL traffic. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Creation or Modification of a new GPO Scheduled Task or Service |
Detects the creation or modification of a new Group Policy based scheduled task or service. These methods are used for legitimate system administration, but can also be abused by an attacker with domain admin permissions to execute a malicious payload remotely on all or a subset of the domain joined machines. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
210 |
Identifies attempts to export a registry hive which may contain credentials using the Windows reg.exe tool. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Sysmon] |
8.13.0 |
211 |
|
Elastic Endgame detected Credential Dumping. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Credential Access] |
None |
103 |
|
Elastic Endgame prevented Credential Dumping. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Credential Access] |
None |
103 |
|
Elastic Endgame detected Credential Manipulation. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
103 |
|
Elastic Endgame prevented Credential Manipulation. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
103 |
|
This rule monitors for (ana)cron jobs being created or renamed. Linux cron jobs are scheduled tasks that can be leveraged by system administrators to set up scheduled tasks, but may be abused by malicious actors for persistence, privilege escalation and command execution. By creating or modifying cron job configurations, attackers can execute malicious commands or scripts at predefined intervals, ensuring their continued presence and enabling unauthorized activities. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
14 |
|
This detection rule addresses multiple vulnerabilities in the CUPS printing system, including CVE-2024-47176, CVE-2024-47076, CVE-2024-47175, and CVE-2024-47177. Specifically, this rule detects shell executions from the foomatic-rip parent process. These flaws impact components like cups-browsed, libcupsfilters, libppd, and foomatic-rip, allowing remote unauthenticated attackers to manipulate IPP URLs or inject malicious data through crafted UDP packets or network spoofing. This can result in arbitrary command execution when a print job is initiated. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Use Case: Vulnerability], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
2 |
|
This rule detects the use of the |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies the occurrence of a CyberArk Privileged Access Security (PAS) error level audit event. The event.code correlates to the CyberArk Vault Audit Action Code. |
[Data Source: CyberArk PAS], [Use Case: Log Auditing], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
102 |
|
Identifies the occurrence of a CyberArk Privileged Access Security (PAS) non-error level audit event which is recommended for monitoring by the vendor. The event.code correlates to the CyberArk Vault Audit Action Code. |
[Data Source: CyberArk PAS], [Use Case: Log Auditing], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
102 |
|
Detects file creation events in the plugin directories for the Yum package manager. In Linux, DNF (Dandified YUM) is a command-line utility used for handling packages on Fedora-based systems, providing functions for installing, updating, upgrading, and removing software along with managing package repositories. Attackers can backdoor DNF to gain persistence by injecting malicious code into plugins that DNF runs, thereby ensuring continued unauthorized access or control each time DNF is used for package management. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies changes to the DNS Global Query Block List (GQBL), a security feature that prevents the resolution of certain DNS names often exploited in attacks like WPAD spoofing. Attackers with certain privileges, such as DNSAdmins, can modify or disable the GQBL, allowing exploitation of hosts running WPAD with default settings for privilege escalation and lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Elastic Endgame] |
8.13.0 |
103 |
|
A machine learning job detected unusually large numbers of DNS queries for a single top-level DNS domain, which is often used for DNS tunneling. DNS tunneling can be used for command-and-control, persistence, or data exfiltration activity. For example, dnscat tends to generate many DNS questions for a top-level domain as it uses the DNS protocol to tunnel data. |
[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |
None |
104 |
|
Identifies when a user enables DNS-over-HTTPS. This can be used to hide internet activity or the process of exfiltrating data. With this enabled, an organization will lose visibility into data such as query type, response, and originating IP, which are used to determine bad actors. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
This rule detects the installation of a Debian package (dpkg) by an unusual parent process. The dpkg command is used to install, remove, and manage Debian packages on a Linux system. Attackers can abuse the dpkg command to install malicious packages on a system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
2 |
|
This rule detects the use of the default Cobalt Strike Team Server TLS certificate. Cobalt Strike is software for Adversary Simulations and Red Team Operations which are security assessments that replicate the tactics and techniques of an advanced adversary in a network. Modifications to the Packetbeat configuration can be made to include MD5 and SHA256 hashing algorithms (the default is SHA1). See the References section for additional information on module configuration. |
[Tactic: Command and Control], [Threat: Cobalt Strike], [Use Case: Threat Detection], [Domain: Endpoint] |
None |
104 |
|
Identifies the execution of commonly abused Windows utilities via a delayed Ping execution. This behavior is often observed during malware installation and is consistent with an attacker attempting to evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies use of the fsutil.exe to delete the volume USNJRNL. This technique is used by attackers to eliminate evidence of files created during post-exploitation activities. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies use of the wbadmin.exe to delete the backup catalog. Ransomware and other malware may do this to prevent system recovery. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Deprecated - Potential Password Spraying of Microsoft 365 User Accounts |
Identifies a high number (25) of failed Microsoft 365 user authentication attempts from a single IP address within 30 minutes, which could be indicative of a password spraying attack. An adversary may attempt a password spraying attack to obtain unauthorized access to user accounts. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |
None |
208 |
Identifies suspicious child processes of the Java interpreter process. This may indicate an attempt to execute a malicious JAR file or an exploitation attempt via a JAVA specific vulnerability. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
209 |
|
This rule identifies the creation of directories in the /bin directory. The /bin directory contains essential binary files that are required for the system to function properly. The creation of directories in this location could be an attempt to hide malicious files or executables, as these /bin directories usually just contain binaries. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
1 |
|
Disable Windows Event and Security Logs Using Built-in Tools |
Identifies attempts to disable EventLog via the logman Windows utility, PowerShell, or auditpol. This is often done by attackers in an attempt to evade detection on a system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
Identifies use of the netsh.exe to disable or weaken the local firewall. Attackers will use this command line tool to disable the firewall during troubleshooting or to enable network mobility. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
User Account Control (UAC) can help mitigate the impact of malware on Windows hosts. With UAC, apps and tasks always run in the security context of a non-administrator account, unless an administrator specifically authorizes administrator-level access to the system. This rule identifies registry value changes to bypass User Access Control (UAC) protection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies use of the Set-MpPreference PowerShell command to disable or weaken certain Windows Defender settings. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies the execution of Linux built-in commands related to account or group enumeration. Adversaries may use account and group information to orient themselves before deciding how to act. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
2 |
|
Identifies the use of built-in tools attackers can use to check for Internet connectivity on compromised systems. These results may be used to determine communication capabilities with C2 servers, or to identify routes, redirectors, and proxy servers. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
102 |
|
This rule identifies a UID change event via |
[Domain: Endpoint], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
1 |
|
Detects when a domain is added to the list of trusted Google Workspace domains. An adversary may add a trusted domain in order to collect and exfiltrate data from their target’s organization with less restrictive security controls. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Defense Evasion], [Resources: Investigation Guide] |
None |
206 |
|
Identifies .lnk shortcut file downloaded from outside the local network. These shortcut files are commonly used in phishing campaigns. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies .url shortcut files downloaded from outside the local network. These shortcut files are commonly used in phishing campaigns. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies the execution of macOS built-in commands used to dump user account hashes. Adversaries may attempt to dump credentials to obtain account login information in the form of a hash. These hashes can be cracked or leveraged for lateral movement. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
106 |
|
Adversaries may dump the content of the keychain storage data from a system to acquire credentials. Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features, including Wi-Fi and website passwords, secure notes, certificates, and Kerberos. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
107 |
|
Detects the copying of the Linux dynamic loader binary and subsequent file creation for the purpose of creating a backup copy. This technique was seen recently being utilized by Linux malware prior to patching the dynamic loader in order to inject and preload a malicious shared object file. This activity should never occur and if it does then it should be considered highly suspicious or malicious. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Orbit], [Data Source: Elastic Defend] |
None |
109 |
|
Detects the creation or modification of files related to the dynamic linker on Linux systems. The dynamic linker is a shared library that is used by the Linux kernel to load and execute programs. Attackers may attempt to hijack the execution flow of a program by modifying the dynamic linker configuration files. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies an AWS Amazon Machine Image (AMI) being shared with another AWS account. Adversaries with access may share an AMI with an external AWS account as a means of data exfiltration. AMIs can contain secrets, bash histories, code artifacts, and other sensitive data that adversaries may abuse if shared with unauthorized accounts. AMIs can be made publicly available accidentally as well. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Threat Detection], [Tactic: Exfiltration] |
None |
2 |
|
Identifies instances where the find command is started on a Linux system with arguments targeting specific VM-related paths, such as "/etc/vmware/", "/usr/lib/vmware/", or "/vmfs/*". These paths are associated with VMware virtualization software, and their presence in the find command arguments may indicate that a threat actor is attempting to search for, analyze, or manipulate VM-related files and configurations on the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
7 |
|
Identifies instances where a process named grep, egrep, or pgrep is started on a Linux system with arguments related to virtual machine (VM) files, such as "vmdk", "vmx", "vmxf", "vmsd", "vmsn", "vswp", "vmss", "nvram", or "vmem". These file extensions are associated with VM-related file formats, and their presence in grep command arguments may indicate that a threat actor is attempting to search for, analyze, or manipulate VM files on the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
7 |
|
Identifies instances where the touch command is executed on a Linux system with the "-r" flag, which is used to modify the timestamp of a file based on another file’s timestamp. The rule targets specific VM-related paths, such as "/etc/vmware/", "/usr/lib/vmware/", or "/vmfs/*". These paths are associated with VMware virtualization software, and their presence in the touch command arguments may indicate that a threat actor is attempting to tamper with timestamps of VM-related files and configurations on the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
8 |
|
Identifies the execution of and EggShell Backdoor. EggShell is a known post exploitation tool for macOS and Linux. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
103 |
|
This rule identifies a sequence of events where a process named |
[Domain: Endpoint], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies the Elastic endpoint agent has stopped and is no longer running on the host. Adversaries may attempt to disable security monitoring tools in an attempt to evade detection or prevention capabilities during an intrusion. This may also indicate an issue with the agent itself and should be addressed to ensure defensive measures are back in a stable state. |
[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies the creation or modification of the Event Monitor Daemon (emond) rules. Adversaries may abuse this service by writing a rule to execute commands when a defined event occurs, such as system start up or user authentication. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies use of the netsh.exe program to enable host discovery via the network. Attackers can use this command-line tool to weaken the host firewall settings. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies registry write modifications to hide an encoded portable executable. This could be indicative of adversary defense evasion by avoiding the storing of malicious content directly on disk. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
311 |
|
Identifies use of WinRar or 7z to create an encrypted files. Adversaries will often compress and encrypt data in preparation for exfiltration. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
113 |
|
Generates a detection alert each time an Elastic Endpoint Security alert is received. Enabling this rule allows you to immediately begin investigating your Endpoint alerts. |
[Data Source: Elastic Defend] |
None |
103 |
|
Identifies device code authentication with an Azure broker client for Entra ID. Adversaries abuse Primary Refresh Tokens (PRTs) to bypass multi-factor authentication (MFA) and gain unauthorized access to Azure resources. PRTs are used in Conditional Access policies to enforce device-based controls. Compromising PRTs allows attackers to bypass these policies and gain unauthorized access. This rule detects successful sign-ins using device code authentication with the Entra ID broker client application ID (29d9ed98-a469-4536-ade2-f981bc1d605e). |
[Domain: Cloud], [Data Source: Azure], [Data Source: Microsoft Entra ID], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |
None |
1 |
|
Identifies the use of dsquery.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate trust relationships that may be used for Lateral Movement opportunities in Windows multi-domain forest environments. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
109 |
|
Identifies the use of nltest.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate domain trusts and gain insight into trust relationships, as well as the state of Domain Controller (DC) replication in a Microsoft Windows NT Domain. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon] |
None |
113 |
|
Identifies native Windows host and network enumeration commands spawned by the Windows Management Instrumentation Provider Service (WMIPrvSE). |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Identifies instances of lower privilege accounts enumerating Administrator accounts or groups using built-in Windows tools. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint] |
None |
114 |
|
Loadable Kernel Modules (or LKMs) are pieces of code that can be loaded and unloaded into the kernel upon demand. They extend the functionality of the kernel without the need to reboot the system. This identifies attempts to enumerate information about a kernel module. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
210 |
|
Loadable Kernel Modules (or LKMs) are pieces of code that can be loaded and unloaded into the kernel upon demand. They extend the functionality of the kernel without the need to reboot the system. This identifies attempts to enumerate information about a kernel module using the /proc/modules filesystem. This filesystem is used by utilities such as lsmod and kmod to list the available kernel modules. |
[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |
None |
107 |
|
Identifies instances of an unusual process enumerating built-in Windows privileged local groups membership like Administrators or Remote Desktop users. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: System] |
8.12.0 |
315 |
|
Identifies the execution of macOS built-in commands related to account or group enumeration. Adversaries may use account and group information to orient themselves before deciding how to act. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |
None |
207 |
|
Identifies the use of the Exchange PowerShell cmdlet, New-MailBoxExportRequest, to export the contents of a primary mailbox or archive to a .pst file. Adversaries may target user email to collect sensitive information. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
8.12.0 |
110 |
|
This rule monitors for the addition of an executable bit for scripts that are located in directories which are commonly abused for persistence. An alert of this rule is an indicator that a persistence mechanism is being set up within your environment. Adversaries may create these scripts to execute malicious code at start-up, or at a set interval to gain persistence onto the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
4 |
|
Masquerading can allow an adversary to evade defenses and better blend in with the environment. One way it occurs is when the name or location of a file is manipulated as a means of tricking a user into executing what they think is a benign file type but is actually executable code. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Identifies the creation or modification of an executable file with an unexpected file extension. Attackers may attempt to evade detection by masquerading files using the file extension values used by image, audio, or document file types. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
2 |
|
Monitors for kernel processes with associated process executable fields that are not empty. Unix kernel processes such as kthreadd and kworker typically do not have process.executable fields associated to them. Attackers may attempt to hide their malicious programs by masquerading as legitimate kernel processes. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
3 |
|
Identifies process execution from suspicious default Windows directories. This may be abused by adversaries to hide malware in trusted paths. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
214 |
|
Identifies process execution from a removable media and by an unusual process. Adversaries may move onto systems, possibly those on disconnected or air-gapped networks, by copying malware to removable media and taking advantage of Autorun features when the media is inserted into a system and executes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Defend] |
None |
3 |
|
Windows Component Object Model (COM) is an inter-process communication (IPC) component of the native Windows application programming interface (API) that enables interaction between software objects or executable code. Xwizard can be used to run a COM object created in registry to evade defensive counter measures. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies an executable created by a Microsoft Office application and subsequently executed. These processes are often launched via scripts inside documents or during exploitation of Microsoft Office applications. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
111 |
|
Identifies a suspicious file that was written by a PDF reader application and subsequently executed. These processes are often launched via exploitation of PDF applications. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Identifies execution of suspicious persistent programs (scripts, rundll32, etc.) by looking at process lineage and command line usage. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
107 |
|
This rule identifies the execution of unsigned executables via service control manager (SCM). Adversaries may abuse SCM to execute malware or escalate privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
105 |
|
Identifies attempts to execute a child process from within the context of an Electron application using the child_process Node.js module. Adversaries may abuse this technique to inherit permissions from parent processes. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies the execution of a command via Microsoft Visual Studio Pre or Post build events. Adversaries may backdoor a trusted visual studio project to execute a malicious command during the project build process. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies execution via MSSQL xp_cmdshell stored procedure. Malicious users may attempt to elevate their privileges by using xp_cmdshell, which is disabled by default, thus, it’s important to review the context of it’s use. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies the execution of DotNet ClickOnce installer via Dfsvc.exe trampoline. Adversaries may take advantage of ClickOnce to proxy execution of malicious payloads via trusted Microsoft processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies execution from the Remote Desktop Protocol (RDP) shared mountpoint tsclient on the target host. This may indicate a lateral movement attempt. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
An adversary can use the Windows command line debugging utility cdb.exe to execute commands or shellcode. This rule looks for those instances and where the cdb.exe binary is outside of the normal WindowsKit installation paths. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
1 |
|
Detects attempts to execute a program on the host from the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
107 |
|
Identifies the creation, change, or deletion of a DLL module within a Windows SxS local folder. Adversaries may abuse shared modules to execute malicious payloads by instructing the Windows module loader to load DLLs from arbitrary local paths. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
208 |
|
Identifies execution of the security_authtrampoline process via a scripting interpreter. This occurs when programs use AuthorizationExecute-WithPrivileges from the Security.framework to run another program with root privileges. It should not be run by itself, as this is a sign of execution with explicit logon credentials. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies an attempt to load a revoked or expired driver. Adversaries may bring outdated drivers with vulnerabilities to gain code execution in kernel mode or abuse revoked certificates to sign their drivers. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
5 |
|
Elastic Endgame detected an Exploit. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation] |
None |
103 |
|
Elastic Endgame prevented an Exploit. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation] |
None |
103 |
|
Identifies the use of the Exchange PowerShell cmdlet, New-MailBoxExportRequest, to export the contents of a primary mailbox or archive to a .pst file. Adversaries may target user email to collect sensitive information. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
8.13.0 |
316 |
|
Generates a detection alert for each external alert written to the configured indices. Enabling this rule allows you to immediately begin investigating external alerts in the app. |
[OS: Windows], [Data Source: APM], [OS: macOS], [OS: Linux] |
None |
103 |
|
Identifies domains commonly used by adversaries for post-exploitation IP lookups. It is common for adversaries to test for Internet access and acquire their external IP address after they have gained access to a system. Among others, this has been observed in campaigns leveraging the information stealer, Trickbot. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
108 |
|
Detects an external Google Workspace user account being added to an existing group. Adversaries may add external user accounts as a means to intercept shared files or emails with that specific group. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Initial Access], [Resources: Investigation Guide] |
None |
3 |
|
Detects files being compressed or archived into common formats. This is a common technique used to obfuscate files to evade detection or to staging data for exfiltration. |
[Data Source: Elastic Defend], [Domain: Endpoint], [OS: macOS], [OS: Windows], [Tactic: Collection], [Rule Type: BBR] |
None |
5 |
|
Identifies modification of a file creation time. Adversaries may modify file time attributes to blend malicious content with existing files. Timestomping is a technique that modifies the timestamps of a file often to mimic files that are in trusted directories. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Sysmon] |
None |
5 |
|
This detection rule addresses multiple vulnerabilities in the CUPS printing system, including CVE-2024-47176, CVE-2024-47076, CVE-2024-47175, and CVE-2024-47177. Specifically, this rule detects suspicious file creation events executed by child processes of foomatic-rip. These flaws impact components like cups-browsed, libcupsfilters, libppd, and foomatic-rip, allowing remote unauthenticated attackers to manipulate IPP URLs or inject malicious data through crafted UDP packets or network spoofing. This can result in arbitrary command execution when a print job is initiated. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Use Case: Vulnerability], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
1 |
|
File Creation, Execution and Self-Deletion in Suspicious Directory |
This rule monitors for the creation of a file, followed by its execution and self-deletion in a short timespan within a directory often used for malicious purposes by threat actors. This behavior is often used by malware to execute malicious code and delete itself to hide its tracks. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
5 |
Malware or other files dropped or created on a system by an adversary may leave traces behind as to what was done within a network and how. Adversaries may remove these files over the course of an intrusion to keep their footprint low or remove them at the end as part of the post-intrusion cleanup process. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
109 |
|
This rule detects when chmod is used to add the execute permission to a file inside a container. Modifying file permissions to make a file executable could indicate malicious activity, as an attacker may attempt to run unauthorized or malicious code inside the container. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion] |
None |
2 |
|
Identifies file permission modifications in common writable directories by a non-root user. Adversaries often drop files or payloads into a writable directory and change permissions prior to execution. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
211 |
|
Identifies files written to the root of the Recycle Bin folder instead of subdirectories. Adversaries may place files in the root of the Recycle Bin in preparation for exfiltration or to evade defenses. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame], [Data Source: Sysmon] |
None |
6 |
|
This rule detects the use of the built-in Linux DebugFS utility from inside a privileged container. DebugFS is a special file system debugging utility which supports reading and writing directly from a hard drive device. When launched inside a privileged container, a container deployed with all the capabilities of the host machine, an attacker can access sensitive host level files which could be used for further privilege escalation and container escapes to the host machine. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
1 |
|
A netcat process is engaging in network activity on a Linux host. Netcat is often used as a persistence mechanism by exporting a reverse shell or by serving a shell on a listening port. Netcat is also sometimes used for data exfiltration. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
110 |
|
Identifies the change of permissions/ownership of files/folders through built-in Windows utilities. Threat actors may require permission modification of files/folders to change, modify or delete them. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
2 |
|
Detects a file being made immutable using the chattr binary. Making a file immutable means it cannot be deleted or renamed, no link can be created to this file, most of the file’s metadata can not be modified, and the file can not be opened in write mode. Threat actors will commonly utilize this to prevent tampering or modification of their malicious files or any system files they have modified for purposes of persistence (e.g .ssh, /etc/passwd, etc.). |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
112 |
|
This rule identifies the execution of commands that can be used to delete files and directories. Adversaries may delete files and directories on a host system, such as logs, browser history, or malware. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies unusual files downloaded from outside the local network that have the potential to be abused for code execution. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
3 |
|
Finder Sync plugins enable users to extend Finder’s functionality by modifying the user interface. Adversaries may abuse this feature by adding a rogue Finder Plugin to repeatedly execute malicious payloads for persistence. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
206 |
|
First Occurrence GitHub Event for a Personal Access Token (PAT) |
Detects a first occurrence event for a personal access token (PAT) not seen in the last 14 days. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
Identifies when a user is observed for the first time in the last 14 days authenticating using the deviceCode protocol. The device code authentication flow can be abused by attackers to phish users and steal access tokens to impersonate the victim. By its very nature, device code should only be used when logging in to devices without keyboards, where it is difficult to enter emails and passwords. |
[Domain: Cloud], [Data Source: Azure], [Data Source: Microsoft Entra ID], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |
None |
1 |
|
Detects an interaction with a private GitHub repository from a new IP address not seen in the last 14 days. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
|
First Occurrence of GitHub User Interaction with Private Repo |
Detects a new private repo interaction for a GitHub user not seen in the last 14 days. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
First Occurrence of IP Address For GitHub Personal Access Token (PAT) |
Detects a new IP address used for a GitHub PAT not previously seen in the last 14 days. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
Detects a new IP address used for a GitHub user not previously seen in the last 14 days. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
|
Identifies the first occurrence of an Okta user session started via a proxy. |
[Tactic: Initial Access], [Use Case: Identity and Access Audit], [Data Source: Okta] |
None |
4 |
|
First Occurrence of Personal Access Token (PAT) Use For a GitHub User |
A new PAT was used for a GitHub user not previously seen in the last 14 days. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
First Occurrence of Private Repo Event from Specific GitHub Personal Access Token (PAT) |
Detects a new private repo interaction for a GitHub PAT not seen in the last 14 days. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
Identifies the first occurrence of an AWS Security Token Service (STS) |
[Domain: Cloud], [Data Source: Amazon Web Services], [Data Source: AWS], [Data Source: AWS STS], [Use Case: Threat Detection], [Tactic: Defense Evasion] |
None |
1 |
|
First Occurrence of User Agent For a GitHub Personal Access Token (PAT) |
Detects a new user agent used for a GitHub PAT not previously seen in the last 14 days. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
Detects a new user agent used for a GitHub user not previously seen in the last 14 days. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
|
This rule detects the first time a principal calls AWS Cloudwatch |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Cloudformation], [Use Case: Asset Visibility], [Tactic: Execution] |
None |
1 |
|
First Time Seen AWS Secret Value Accessed in Secrets Manager |
An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service may attempt to leverage the compromised service to access secrets in AWS Secrets Manager. This rule looks for the first time a specific user identity has programmatically retrieved a secret value from Secrets Manager using the |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Secrets Manager], [Tactic: Credential Access], [Resources: Investigation Guide] |
None |
312 |
First Time Seen Commonly Abused Remote Access Tool Execution |
Adversaries may install legitimate remote access tools (RAT) to compromised endpoints for further command-and-control (C2). Adversaries can rely on installed RATs for persistence, execution of native commands and more. This rule detects when a process is started whose name or code signature resembles commonly abused RATs. This is a New Terms rule type indicating the host has not seen this RAT process started before within the last 30 days. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: System] |
None |
8 |
Identifies the load of a driver with an original file name and signature values that were observed for the first time during the last 30 days. This rule type can help baseline drivers installation within your environment. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
8 |
|
First Time Seen Google Workspace OAuth Login from Third-Party Application |
Detects the first time a third-party application logs in and authenticated with OAuth. OAuth is used to grant permissions to specific resources and services in Google Workspace. Compromised credentials or service accounts could allow an adversary to authenticate to Google Workspace as a valid user and inherit their privileges. |
[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Defense Evasion], [Tactic: Initial Access] |
None |
5 |
Identifies a new credentials logon type performed by an unusual process. This may indicate the existence of an access token forging capability that are often abused to bypass access control restrictions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: System] |
None |
5 |
|
Identifies newly seen removable devices by device friendly name using registry modification events. While this activity is not inherently malicious, analysts can use those events to aid monitoring for data exfiltration over those devices. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Exfiltration], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
109 |
|
This rule identifies when a User Account starts the Active Directory Replication Process for the first time. Attackers can use the DCSync technique to get credential information of individual accounts or the entire domain, thus compromising the entire domain. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Resources: Investigation Guide], [Data Source: System] |
None |
13 |
|
Identifies the occurrence of a security alert from the Google Workspace alerts center. Google Workspace’s security alert center provides an overview of actionable alerts that may be affecting an organization’s domain. An alert is a warning of a potential security issue that Google has detected. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Log Auditing], [Use Case: Threat Detection] |
None |
3 |
|
Identifies the enable of the full user-mode dumps feature system-wide. This feature allows Windows Error Reporting (WER) to collect data after an application crashes. This setting is a requirement for the LSASS Shtinkering attack, which fakes the communication of a crash on LSASS, generating a dump of the process memory, which gives the attacker access to the credentials present on the system without having to bring malware to the system. This setting is not enabled by default, and applications must create their registry subkeys to hold settings that enable them to collect dumps. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
8 |
|
Identifies when a firewall rule is created in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be configured to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may create a new firewall rule in order to weaken their target’s security controls and allow more permissive ingress or egress traffic flows for their benefit. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies when a firewall rule is deleted in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be configured to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may delete a firewall rule in order to weaken their target’s security controls. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies when a firewall rule is modified in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be modified to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may modify an existing firewall rule in order to weaken their target’s security controls and allow more permissive ingress or egress traffic flows for their benefit. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies an Identity and Access Management (IAM) custom role creation in Google Cloud Platform (GCP). Custom roles are user-defined, and allow for the bundling of one or more supported permissions to meet specific needs. Custom roles will not be updated automatically and could lead to privilege creep if not carefully scrutinized. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |
None |
104 |
|
Identifies an Identity and Access Management (IAM) role deletion in Google Cloud Platform (GCP). A role contains a set of permissions that allows you to perform specific actions on Google Cloud resources. An adversary may delete an IAM role to inhibit access to accounts utilized by legitimate users. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Impact] |
None |
104 |
|
Identifies the deletion of an Identity and Access Management (IAM) service account key in Google Cloud Platform (GCP). Each service account is associated with two sets of public/private RSA key pairs that are used to authenticate. If a key is deleted, the application will no longer be able to access Google Cloud resources using that key. A security best practice is to rotate your service account keys regularly. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
104 |
|
Identifies a Logging bucket deletion in Google Cloud Platform (GCP). Log buckets are containers that store and organize log data. A deleted bucket stays in a pending state for 7 days, and Logging continues to route logs to the bucket during that time. To stop routing logs to a deleted bucket, you can delete the log sinks that have the bucket as their destination, or modify the filter for the sinks to stop it from routing logs to the deleted bucket. An adversary may delete a log bucket to evade detection. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies a Logging sink deletion in Google Cloud Platform (GCP). Every time a log entry arrives, Logging compares the log entry to the sinks in that resource. Each sink whose filter matches the log entry writes a copy of the log entry to the sink’s export destination. An adversary may delete a Logging sink to evade detection. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies a modification to a Logging sink in Google Cloud Platform (GCP). Logging compares the log entry to the sinks in that resource. Each sink whose filter matches the log entry writes a copy of the log entry to the sink’s export destination. An adversary may update a Logging sink to exfiltrate logs to a different export destination. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Exfiltration] |
None |
104 |
|
Identifies the creation of a subscription in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A subscription is a named resource representing the stream of messages to be delivered to the subscribing application. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Collection] |
None |
105 |
|
Identifies the deletion of a subscription in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A subscription is a named resource representing the stream of messages to be delivered to the subscribing application. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies the creation of a topic in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A topic is used to forward messages from publishers to subscribers. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Collection] |
None |
105 |
|
Identifies the deletion of a topic in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A publisher application creates and sends messages to a topic. Deleting a topic can interrupt message flow in the Pub/Sub pipeline. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies when a new service account is created in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. If service accounts are not tracked and managed properly, they can present a security risk. An adversary may create a new service account to use during their operations in order to avoid using a standard user account and attempt to evade detection. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
104 |
|
Identifies when a service account is deleted in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. An adversary may delete a service account in order to disrupt their target’s business operations. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Impact] |
None |
104 |
|
Identifies when a service account is disabled in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. An adversary may disable a service account in order to disrupt to disrupt their target’s business operations. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Impact] |
None |
104 |
|
Identifies when a new key is created for a service account in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. If private keys are not tracked and managed properly, they can present a security risk. An adversary may create a new key for a service account in order to attempt to abuse the permissions assigned to that account and evade detection. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
104 |
|
Identifies when the configuration is modified for a storage bucket in Google Cloud Platform (GCP). An adversary may modify the configuration of a storage bucket in order to weaken the security controls of their target’s environment. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies when a Google Cloud Platform (GCP) storage bucket is deleted. An adversary may delete a storage bucket in order to disrupt their target’s business operations. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Tactic: Impact] |
None |
104 |
|
Identifies when the Identity and Access Management (IAM) permissions are modified for a Google Cloud Platform (GCP) storage bucket. An adversary may modify the permissions on a storage bucket to weaken their target’s security controls or an administrator may inadvertently modify the permissions, which could lead to data exposure or loss. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies when a Virtual Private Cloud (VPC) network is deleted in Google Cloud Platform (GCP). A VPC network is a virtual version of a physical network within a GCP project. Each VPC network has its own subnets, routes, and firewall, as well as other elements. An adversary may delete a VPC network in order to disrupt their target’s network and business operations. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies when a virtual private cloud (VPC) route is created in Google Cloud Platform (GCP). Google Cloud routes define the paths that network traffic takes from a virtual machine (VM) instance to other destinations. These destinations can be inside a Google VPC network or outside it. An adversary may create a route in order to impact the flow of network traffic in their target’s cloud environment. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
104 |
|
Identifies when a Virtual Private Cloud (VPC) route is deleted in Google Cloud Platform (GCP). Google Cloud routes define the paths that network traffic takes from a virtual machine (VM) instance to other destinations. These destinations can be inside a Google VPC network or outside it. An adversary may delete a route in order to impact the flow of network traffic in their target’s cloud environment. |
[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
104 |
|
This rule detects child processes spawned by Git hooks. Git hooks are scripts that Git executes before or after events such as commit, push, and receive. The rule identifies child processes spawned by Git hooks that are not typically spawned by the Git process itself. This behavior may indicate an attacker attempting to hide malicious activity by leveraging the legitimate Git process to execute unauthorized commands. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
2 |
|
This rule detects the execution of a potentially malicious process from a Git hook. Git hooks are scripts that Git executes before or after events such as: commit, push, and receive. An attacker can abuse Git hooks to execute arbitrary commands on the system and establish persistence. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
2 |
|
This rule detects the creation or modification of a Git hook file on a Linux system. Git hooks are scripts that Git executes before or after events such as commit, push, and receive. They are used to automate tasks, enforce policies, and customize Git’s behavior. Attackers can abuse Git hooks to maintain persistence on a system by executing malicious code whenever a specific Git event occurs. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
3 |
|
This rule detects a suspicious egress network connection attempt from a Git hook script. Git hooks are scripts that Git executes before or after events such as: commit, push, and receive. An attacker can abuse these features to execute arbitrary commands on the system, establish persistence or to initialize a network connection to a remote server and exfiltrate data or download additional payloads. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
2 |
|
Detects the deletion of a GitHub app either from a repo or an organization. |
[Domain: Cloud], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Github] |
8.12.0 |
103 |
|
This rule detects when a member is granted the organization owner role of a GitHub organization. This role provides admin level privileges. Any new owner role should be investigated to determine its validity. Unauthorized owner roles could indicate compromise within your organization and provide unlimited access to data and settings. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Data Source: Github] |
8.12.0 |
105 |
|
Access to private GitHub organization resources was revoked for a PAT. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
|
This rule detects setting modifications for protected branches of a GitHub repository. Branch protection rules can be used to enforce certain workflows or requirements before a contributor can push changes to a branch in your repository. Changes to these protected branch settings should be investigated and verified as legitimate activity. Unauthorized changes could be used to lower your organization’s security posture and leave you exposed for future attacks. |
[Domain: Cloud], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Github] |
8.12.0 |
105 |
|
A new GitHub repository was created. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
|
This rule detects when a GitHub repository is deleted within your organization. Repositories are a critical component used within an organization to manage work, collaborate with others and release products to the public. Any delete action against a repository should be investigated to determine it’s validity. Unauthorized deletion of organization repositories could cause irreversible loss of intellectual property and indicate compromise within your organization. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Data Source: Github] |
8.12.0 |
102 |
|
This rule is part of the "GitHub UEBA - Unusual Activity from Account Pack", and leverages alert data to determine when multiple alerts are executed by the same user in a timespan of one hour. Analysts can use this to prioritize triage and response, as these alerts are a higher indicator of compromised user accounts or PATs. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: Higher-Order Rule], [Data Source: Github] |
None |
1 |
|
A GitHub user was blocked from access to an organization. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
|
Drive and Docs is a Google Workspace service that allows users to leverage Google Drive and Google Docs. Access to files is based on inherited permissions from the child organizational unit the user belongs to which is scoped by administrators. Typically if a user is removed, their files can be transferred to another user by the administrator. This service can also be abused by adversaries to transfer files to an adversary account for potential exfiltration. |
[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Collection], [Resources: Investigation Guide] |
None |
107 |
|
Google Workspace admins may setup 2-step verification (2SV) to add an extra layer of security to user accounts by asking users to verify their identity when they use login credentials. Admins have the ability to enforce 2SV from the admin console as well as the methods acceptable for verification and enrollment period. 2SV requires enablement on admin accounts prior to it being enabled for users within organization units. Adversaries may disable 2SV to lower the security requirements to access a valid account. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
107 |
|
Google Workspace API Access Granted via Domain-Wide Delegation |
Detects when a domain-wide delegation of authority is granted to a service account. Domain-wide delegation can be configured to grant third-party and internal applications to access the data of Google Workspace users. An adversary may configure domain-wide delegation to maintain access to their target’s data. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |
None |
207 |
Assigning the administrative role to a user will grant them access to the Google Admin console and grant them administrator privileges which allow them to access and manage various resources and applications. An adversary may create a new administrator account for persistence or apply the admin role to an existing user to carry out further intrusion efforts. Users with super-admin privileges can bypass single-sign on if enabled in Google Workspace. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
207 |
|
Detects when a custom admin role is deleted. An adversary may delete a custom admin role in order to impact the permissions or capabilities of system administrators. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Impact], [Resources: Investigation Guide] |
None |
206 |
|
Google Workspace administrators whom manage Windows devices and have Windows device management enabled may also enable BitLocker drive encryption to mitigate unauthorized data access on lost or stolen computers. Adversaries with valid account access may disable BitLocker to access sensitive data on an endpoint added to Google Workspace device management. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Defense Evasion], [Resources: Investigation Guide] |
None |
107 |
|
Detects when a custom admin role is created in Google Workspace. An adversary may create a custom admin role in order to elevate the permissions of other user accounts and persist in their target’s environment. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |
None |
206 |
|
Detects when a custom Gmail route is added or modified in Google Workspace. Adversaries can add a custom e-mail route for outbound mail to route these e-mails to their own inbox of choice for data gathering. This allows adversaries to capture sensitive information from e-mail and potential attachments, such as invoices or payment documents. By default, all email from current Google Workspace users with accounts are routed through a domain’s mail server for inbound and outbound mail. |
[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Collection], [Resources: Investigation Guide] |
None |
107 |
|
Google Workspace Drive Encryption Key(s) Accessed from Anonymous User |
Detects when an external (anonymous) user has viewed, copied or downloaded an encryption key file from a Google Workspace drive. Adversaries may gain access to encryption keys stored in private drives from rogue access links that do not have an expiration. Access to encryption keys may allow adversaries to access sensitive data or authenticate on behalf of users. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Credential Access] |
None |
4 |
Detects when multi-factor authentication (MFA) enforcement is disabled for Google Workspace users. An adversary may disable MFA enforcement in order to weaken an organization’s security controls. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Impact], [Resources: Investigation Guide] |
None |
208 |
|
Google Workspace Object Copied to External Drive with App Consent |
Detects when a user copies a Google spreadsheet, form, document or script from an external drive. Sequence logic has been added to also detect when a user grants a custom Google application permission via OAuth shortly after. An adversary may send a phishing email to the victim with a Drive object link where "copy" is included in the URI, thus copying the object to the victim’s drive. If a container-bound script exists within the object, execution will require permission access via OAuth in which the user has to accept. |
[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Initial Access], [Resources: Investigation Guide] |
None |
7 |
Detects when a Google Workspace password policy is modified. An adversary may attempt to modify a password policy in order to weaken an organization’s security controls. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
206 |
|
Google Workspace Restrictions for Marketplace Modified to Allow Any App |
Detects when the Google Marketplace restrictions are changed to allow any application for users in Google Workspace. Malicious APKs created by adversaries may be uploaded to the Google marketplace but not installed on devices managed within Google Workspace. Administrators should set restrictions to not allow any application from the marketplace for security reasons. Adversaries may enable any app to be installed and executed on mobile devices within a Google Workspace environment prior to distributing the malicious APK to the end user. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Defense Evasion], [Resources: Investigation Guide] |
None |
108 |
Detects when a custom admin role or its permissions are modified. An adversary may modify a custom admin role in order to elevate the permissions of other user accounts and persist in their target’s environment. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |
None |
206 |
|
Detects when a previously suspended user’s account is renewed in Google Workspace. An adversary may renew a suspended user account to maintain access to the Google Workspace organization with a valid account. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |
None |
3 |
|
Users in Google Workspace are typically assigned a specific organizational unit that grants them permissions to certain services and roles that are inherited from this organizational unit. Adversaries may compromise a valid account and change which organizational account the user belongs to which then could allow them to inherit permissions to applications and resources inaccessible prior to. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
107 |
|
Detects the first occurrence of a modification to Group Policy Object Attributes to add privileges to user accounts or use them to add users as local admins. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
111 |
|
Detects the usage of gpresult.exe to query group policy objects. Attackers may query group policy objects during the reconnaissance phase after compromising a system to gain a better understanding of the active directory environment and possible methods to escalate privileges or move laterally. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
109 |
|
Halfbaked is a malware family used to establish persistence in a contested network. This rule detects a network activity algorithm leveraged by Halfbaked implant beacons for command and control. |
[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |
None |
104 |
|
This rule detects the creation of a hidden directory via an unusual parent executable. Hidden directories are directories that are not visible to the user by default. They are often used by attackers to hide malicious files or tools. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Tactic: Persistence] |
None |
1 |
|
Identify activity related where adversaries can add the hidden flag to files to hide them from the user in an attempt to evade detection. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
A machine learning job has detected unusually high number of process arguments in an RDP session. Executing sophisticated attacks such as lateral movement can involve the use of complex commands, obfuscation mechanisms, redirection and piping, which in turn increases the number of arguments in a command. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
A machine learning job has detected unusually high mean of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
Detects a high number of unique private repo clone events originating from a single personal access token within a short time period. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Data Source: Github] |
8.12.0 |
103 |
|
High Number of Okta Device Token Cookies Generated for Authentication |
Detects when an Okta client address has a certain threshold of Okta user authentication events with multiple device token hashes generated for single user authentication. Adversaries may attempt to launch a credential stuffing or password spraying attack from the same device by using a list of known usernames and passwords to gain unauthorized access to user accounts. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Credential Access] |
8.13.0 |
3 |
Identifies a high number of Okta user password reset or account unlock attempts. An adversary may attempt to obtain unauthorized access to Okta user accounts using these methods and attempt to blend in with normal activity in their target’s environment and evade detection. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Defense Evasion] |
None |
211 |
|
This rule identifies a high number (10) of process terminations via pkill from the same host within a short time period. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
112 |
|
This rule identifies a high number (10) of process terminations (stop, delete, or suspend) from the same host within a short time period. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System] |
None |
112 |
|
A machine learning job has detected unusually high variance of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
Detects files creation and modification on the host system from the the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
7 |
|
The hosts file on endpoints is used to control manual IP address to hostname resolutions. The hosts file is the first point of lookup for DNS hostname resolution so if adversaries can modify the endpoint hosts file, they can route traffic to malicious infrastructure. This rule detects modifications to the hosts file on Microsoft Windows, Linux (Ubuntu or RHEL) and macOS systems. |
[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
110 |
|
Hping ran on a Linux host. Hping is a FOSS command-line packet analyzer and has the ability to construct network packets for a wide variety of network security testing applications, including scanning and firewall auditing. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
108 |
|
Identifies when Internet Information Services (IIS) HTTP Logging is disabled on a server. An attacker with IIS server access via a webshell or other mechanism can disable HTTP Logging as an effective anti-forensics measure. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
This rule detects events that could be describing IPSEC NAT Traversal traffic. IPSEC is a VPN technology that allows one system to talk to another using encrypted tunnels. NAT Traversal enables these tunnels to communicate over the Internet where one of the sides is behind a NAT router gateway. This may be common on your network, but this technique is also used by threat actors to avoid detection. |
[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection], [Data Source: PAN-OS] |
None |
105 |
|
This rule monitors for the execution of commands that enable IPv4 and IPv6 forwarding on Linux systems. Enabling IP forwarding can be used to route network traffic between different network interfaces, potentially allowing attackers to pivot between networks, exfiltrate data, or establish command and control channels. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
1 |
|
The Debugger and SilentProcessExit registry keys can allow an adversary to intercept the execution of files, causing a different process to be executed. This functionality can be abused by an adversary to establish persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Identifies binaries that are loaded and with an invalid code signature. This may indicate an attempt to masquerade as a signed binary. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies abuse of the Windows Update Auto Update Client (wuauclt.exe) to load an arbitrary DLL. This behavior is used as a defense evasion technique to blend-in malicious activity with legitimate Windows software. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Identifies Elasticsearch nodes that do not have Transport Layer Security (TLS), and/or lack authentication, and are accepting inbound network connections over the default Elasticsearch port. |
[Use Case: Threat Detection], [Tactic: Initial Access], [Domain: Endpoint] |
None |
104 |
|
Identifies the use of Distributed Component Object Model (DCOM) to execute commands from a remote host, which are launched via the HTA Application COM Object. This behavior may indicate an attacker abusing a DCOM application to move laterally while attempting to evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
107 |
|
Identifies the use of Distributed Component Object Model (DCOM) to run commands from a remote host, which are launched via the MMC20 Application COM Object. This behavior may indicate an attacker abusing a DCOM application to move laterally. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Incoming DCOM Lateral Movement with ShellBrowserWindow or ShellWindows |
Identifies use of Distributed Component Object Model (DCOM) to run commands from a remote host, which are launched via the ShellBrowserWindow or ShellWindows Application COM Object. This behavior may indicate an attacker abusing a DCOM application to stealthily move laterally. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
107 |
Identifies remote execution via Windows PowerShell remoting. Windows PowerShell remoting allows a user to run any Windows PowerShell command on one or more remote computers. This could be an indication of lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
109 |
|
Identifies remote execution via Windows Remote Management (WinRM) remote shell on a target host. This could be an indication of lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Identifies indirect command execution via Program Compatibility Assistant (pcalua.exe) or forfiles.exe. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame], [Data Source: System] |
None |
4 |
|
Identifies downloads of executable and archive files via the Windows Background Intelligent Transfer Service (BITS). Adversaries could leverage Windows BITS transfer jobs to download remote payloads. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
8 |
|
Identifies when a specified inbound (ingress) rule is added or adjusted for a VPC security group in AWS EC2. This rule detects when a security group rule is added that allows traffic from any IP address or from a specific IP address to common remote access ports, such as 22 (SSH) or 3389 (RDP). Adversaries may add these rules to allow remote access to VPC instances from any location, increasing the attack surface and potentially exposing the instances to unauthorized access. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Threat Detection], [Tactic: Defense Evasion] |
None |
1 |
|
InstallUtil is a command-line utility that allows for installation and uninstallation of resources by executing specific installer components specified in .NET binaries. Adversaries may use InstallUtil to proxy the execution of code through a trusted Windows utility. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame], [Data Source: System] |
None |
4 |
|
Identifies InstallUtil.exe making outbound network connections. This may indicate adversarial activity as InstallUtil is often leveraged by adversaries to execute code and evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
107 |
|
Identifies the installation of custom Application Compatibility Shim databases. This Windows functionality has been abused by attackers to stealthily gain persistence and arbitrary code execution in legitimate Windows processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Elastic Endgame] |
8.13.0 |
209 |
|
Identifies registry modifications related to the Windows Security Support Provider (SSP) configuration. Adversaries may abuse this to establish persistence in an environment. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Interactive Exec Command Launched Against A Running Container |
This rule detects interactive exec events launched against a container using the exec command. Using the exec command in a pod allows a user to establish a temporary shell session and execute any process/command inside the container. This rule specifically targets higher-risk interactive commands that allow real-time interaction with a container’s shell. A malicious actor could use this level of access to further compromise the container environment or attempt a container breakout. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |
None |
2 |
Identifies interactive logon attempt with alternate credentials and by an unusual process. Adversaries may create a new token to escalate privileges and bypass access controls. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: System] |
None |
4 |
|
Identifies when a terminal (tty) is spawned via Perl. Attackers may upgrade a simple reverse shell to a fully interactive tty after obtaining initial access to a host. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
108 |
|
Identifies when a terminal (tty) is spawned via Python. Attackers may upgrade a simple reverse shell to a fully interactive tty after obtaining initial access to a host. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
110 |
|
Identifies the modification of the msDS-AllowedToDelegateTo attribute to KRBTGT. Attackers can use this technique to maintain persistence to the domain by having the ability to request tickets for the KRBTGT service. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Data Source: System] |
None |
108 |
|
Identifies the use of the Kerberos credential cache (kcc) utility to dump locally cached Kerberos tickets. Adversaries may attempt to dump credential material in the form of tickets that can be leveraged for lateral movement. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies the modification of an account’s Kerberos pre-authentication options. An adversary with GenericWrite/GenericAll rights over the account can maliciously modify these settings to perform offline password cracking attacks such as AS-REP roasting. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Data Source: System] |
None |
113 |
|
Identifies network connections to the standard Kerberos port from an unusual process. On Windows, the only process that normally performs Kerberos traffic from a domain joined host is lsass.exe. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Detects the loading of a Linux kernel module through system calls. Threat actors may leverage Linux kernel modules to load a rootkit on a system providing them with complete control and the ability to hide from security products. As other rules monitor for the addition of Linux kernel modules through system utilities or .ko files, this rule covers the gap that evasive rootkits leverage by monitoring for kernel module additions on the lowest level through auditd_manager. |
[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |
None |
4 |
|
Detects the loading of a Linux kernel module by a non-root user through system calls. Threat actors may leverage Linux kernel modules to load a rootkit on a system providing them with complete control and the ability to hide from security products. As other rules monitor for the addition of Linux kernel modules through system utilities or .ko files, this rule covers the gap that evasive rootkits leverage by monitoring for kernel module additions on the lowest level through auditd_manager. |
[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |
None |
3 |
|
This detection rule identifies the usage of kexec, helping to uncover unauthorized kernel replacements and potential compromise of the system’s integrity. Kexec is a Linux feature that enables the loading and execution of a different kernel without going through the typical boot process. Malicious actors can abuse kexec to bypass security measures, escalate privileges, establish persistence or hide their activities by loading a malicious kernel, enabling them to tamper with the system’s trusted state, allowing e.g. a VM Escape. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
7 |
|
Detects the use of the insmod binary to load a Linux kernel object file. Threat actors can use this binary, given they have root privileges, to load a rootkit on a system providing them with complete control and the ability to hide from security products. Manually loading a kernel module in this manner should not be at all common and can indicate suspcious or malicious behavior. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Rootkit], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
110 |
|
Kernel modules are pieces of code that can be loaded and unloaded into the kernel upon demand. They extend the functionality of the kernel without the need to reboot the system. This rule identifies attempts to remove a kernel module. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
110 |
|
Adversaries may collect keychain storage data from a system to in order to acquire credentials. Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features, including Wi-Fi and website passwords, secure notes, certificates, and Kerberos. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
108 |
|
Identifies the creation of .kirbi files. The creation of this kind of file is an indicator of an attacker running Kerberos ticket dump utilities, such as Mimikatz, and precedes attacks such as Pass-The-Ticket (PTT), which allows the attacker to impersonate users using Kerberos tickets. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: Elastic Endgame] |
8.13.0 |
210 |
|
This rule detects when an unauthenticated user request is authorized within the cluster. Attackers may attempt to use anonymous accounts to gain initial access to the cluster or to avoid attribution of their activities within the cluster. This rule excludes the /healthz, /livez and /readyz endpoints which are commonly accessed anonymously. |
[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Initial Access], [Tactic: Defense Evasion] |
None |
6 |
|
Kubernetes Container Created with Excessive Linux Capabilities |
This rule detects a container deployed with one or more dangerously permissive Linux capabilities. An attacker with the ability to deploy a container with added capabilities could use this for further execution, lateral movement, or privilege escalation within a cluster. The capabilities detected in this rule have been used in container escapes to the host machine. |
[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |
None |
5 |
This rule detects when a service account makes an unauthorized request for resources from the API server. Service accounts follow a very predictable pattern of behavior. A service account should never send an unauthorized request to the API server. This behavior is likely an indicator of compromise or of a problem within the cluster. An adversary may have gained access to credentials/tokens and this could be an attempt to access or create resources to facilitate further movement or execution within the cluster. |
[Data Source: Kubernetes], [Tactic: Discovery] |
None |
5 |
|
This rule detects an attempt to create or modify a service as type NodePort. The NodePort service allows a user to externally expose a set of labeled pods to the internet. This creates an open port on every worker node in the cluster that has a pod for that service. When external traffic is received on that open port, it directs it to the specific pod through the service representing it. A malicious user can configure a service as type Nodeport in order to intercept traffic from other pods or nodes, bypassing firewalls and other network security measures configured for load balancers within a cluster. This creates a direct method of communication between the cluster and the outside world, which could be used for more malicious behavior and certainly widens the attack surface of your cluster. |
[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Persistence] |
None |
203 |
|
This rule detects an attempt to create or modify a pod using the host IPC namespace. This gives access to data used by any pod that also use the hosts IPC namespace. If any process on the host or any processes in a pod uses the hosts inter-process communication mechanisms (shared memory, semaphore arrays, message queues, etc.), an attacker can read/write to those same mechanisms. They may look for files in /dev/shm or use ipcs to check for any IPC facilities being used. |
[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |
None |
204 |
|
This rules detects an attempt to create or modify a pod attached to the host network. HostNetwork allows a pod to use the node network namespace. Doing so gives the pod access to any service running on localhost of the host. An attacker could use this access to snoop on network activity of other pods on the same node or bypass restrictive network policies applied to its given namespace. |
[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |
None |
204 |
|
This rule detects an attempt to create or modify a pod attached to the host PID namespace. HostPID allows a pod to access all the processes running on the host and could allow an attacker to take malicious action. When paired with ptrace this can be used to escalate privileges outside of the container. When paired with a privileged container, the pod can see all of the processes on the host. An attacker can enter the init system (PID 1) on the host. From there, they could execute a shell and continue to escalate privileges to root. |
[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |
None |
204 |
|
This rule detects when a pod is created with a sensitive volume of type hostPath. A hostPath volume type mounts a sensitive file or folder from the node to the container. If the container gets compromised, the attacker can use this mount for gaining access to the node. There are many ways a container with unrestricted access to the host filesystem can escalate privileges, including reading data from other containers, and accessing tokens of more privileged pods. |
[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |
None |
204 |
|
This rule detects when a user creates a pod/container running in privileged mode. A highly privileged container has access to the node’s resources and breaks the isolation between containers. If compromised, an attacker can use the privileged container to gain access to the underlying host. Gaining access to the host may provide the adversary with the opportunity to achieve follow-on objectives, such as establishing persistence, moving laterally within the environment, or setting up a command and control channel on the host. |
[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |
None |
204 |
|
Kubernetes Suspicious Assignment of Controller Service Account |
This rule detects a request to attach a controller service account to an existing or new pod running in the kube-system namespace. By default, controllers running as part of the API Server utilize admin-equivalent service accounts hosted in the kube-system namespace. Controller service accounts aren’t normally assigned to running pods and could indicate adversary behavior within the cluster. An attacker that can create or modify pods or pod controllers in the kube-system namespace, can assign one of these admin-equivalent service accounts to a pod and abuse their powerful token to escalate privileges and gain complete cluster control. |
[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |
None |
6 |
This rule detects when a service account or node attempts to enumerate their own permissions via the selfsubjectaccessreview or selfsubjectrulesreview APIs. This is highly unusual behavior for non-human identities like service accounts and nodes. An adversary may have gained access to credentials/tokens and this could be an attempt to determine what privileges they have to facilitate further movement or execution within the cluster. |
[Data Source: Kubernetes], [Tactic: Discovery] |
None |
203 |
|
This rule detects a user attempt to establish a shell session into a pod using the exec command. Using the exec command in a pod allows a user to establish a temporary shell session and execute any process/commands in the pod. An adversary may call bash to gain a persistent interactive shell which will allow access to any data the pod has permissions to, including secrets. |
[Data Source: Kubernetes], [Tactic: Execution] |
None |
203 |
|
Identifies the creation of a Local Security Authority Subsystem Service (lsass.exe) default memory dump. This may indicate a credential access attempt via trusted system utilities such as Task Manager (taskmgr.exe) and SQL Dumper (sqldumper.exe) or known pentesting tools such as Dumpert and AndrewSpecial. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies handle requests for the Local Security Authority Subsystem Service (LSASS) object access with specific access masks that many tools with a capability to dump memory to disk use (0x1fffff, 0x1010, 0x120089). This rule is tool agnostic as it has been validated against a host of various LSASS dump tools such as SharpDump, Procdump, Mimikatz, Comsvcs etc. It detects this behavior at a low level and does not depend on a specific tool or dump file name. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: System] |
None |
111 |
|
Identifies access attempts to the LSASS handle, which may indicate an attempt to dump credentials from LSASS memory. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint] |
None |
10 |
|
Identifies suspicious file creations in the startup folder of a remote system. An adversary could abuse this to move laterally by dropping a malicious script or executable that will be executed after a reboot or user logon. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
An adversary can establish persistence by installing a new launch agent that executes at login by using launchd or launchctl to load a plist into the appropriate directories. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
106 |
|
Indicates the creation or modification of a launch daemon, which adversaries may use to repeatedly execute malicious payloads as part of persistence. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
106 |
|
This rule monitors for the usage of the most common clipboard utilities on unix systems by an uncommon process group leader. Adversaries may collect data stored in the clipboard from users copying information within or between applications. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
5 |
|
Identifies attempts to create a new group. Attackers may create new groups to establish persistence on a system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
6 |
|
This rule monitors for potential memory dumping through gdb. Attackers may leverage memory dumping techniques to attempt secret extraction from privileged processes. Tools that display this behavior include "truffleproc" and "bash-memory-dump". This behavior should not happen by default, and should be investigated thoroughly. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
Identifies the abuse of a Linux binary to break out of a restricted shell or environment by spawning an interactive system shell. The activity of spawning a shell from a binary is not common behavior for a user or system administrator, and may indicate an attempt to evade detection, increase capabilities or enhance the stability of an adversary. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
113 |
|
This rule monitors for X11 forwarding via SSH. X11 forwarding is a feature that allows users to run graphical applications on a remote server and display the application’s graphical user interface on their local machine. Attackers can abuse X11 forwarding for tunneling their GUI-based tools, pivot through compromised systems, and create covert communication channels, enabling lateral movement and facilitating remote control of systems within a network. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
4 |
|
Enrich process events with uname and other command lines that imply Linux system information discovery. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
Identifies attempts to create new users. Attackers may add new users to establish persistence on a system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
6 |
|
Identifies attempts to add a user to a privileged group. Attackers may add users to a privileged group in order to establish persistence on a system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
8 |
|
This rule monitors for the potential memory dump of the init process (PID 1) through gdb. Attackers may leverage memory dumping techniques to attempt secret extraction from privileged processes. Tools that display this behavior include "truffleproc" and "bash-memory-dump". This behavior should not happen by default, and should be investigated thoroughly. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
6 |
|
Identifies registry modification to the LocalAccountTokenFilterPolicy policy. If this value exists (which doesn’t by default) and is set to 1, then remote connections from all local members of Administrators are granted full high-integrity tokens during negotiation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
212 |
|
Indicates the creation of a scheduled task. Adversaries can use these to establish persistence, move laterally, and/or escalate privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
MFA Deactivation with no Re-Activation for Okta User Account |
Detects multi-factor authentication (MFA) deactivation with no subsequent re-activation for an Okta user account. An adversary may deactivate MFA for an Okta user account in order to weaken the authentication requirements for the account. |
[Tactic: Persistence], [Use Case: Identity and Access Audit], [Data Source: Okta], [Domain: Cloud] |
None |
211 |
Detects when multi-factor authentication (MFA) is disabled for a Google Workspace organization. An adversary may attempt to modify a password policy in order to weaken an organization’s security controls. |
[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
206 |
|
Microsoft Office Products offer options for users and developers to control the security settings for running and using Macros. Adversaries may abuse these security settings to modify the default behavior of the Office Application to trust future macros and/or disable security warnings, which could increase their chances of establishing persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
208 |
|
Detects the execution of a MacOS installer package with an abnormal child process (e.g bash) followed immediately by a network connection via a suspicious process (e.g curl). Threat actors will build and distribute malicious MacOS installer packages, which have a .pkg extension, many times imitating valid software in order to persuade and infect their victims often using the package files (e.g pre/post install scripts etc.) to download additional tools or malicious software. If this rule fires it should indicate the installation of a malicious or suspicious package. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
107 |
|
Machine Learning Detected DGA activity using a known SUNBURST DNS domain |
A supervised machine learning model has identified a DNS question name that used by the SUNBURST malware and is predicted to be the result of a Domain Generation Algorithm. |
[Domain: Network], [Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |
None |
5 |
Machine Learning Detected a DNS Request Predicted to be a DGA Domain |
A supervised machine learning model has identified a DNS question name that is predicted to be the result of a Domain Generation Algorithm (DGA), which could indicate command and control network activity. |
[Domain: Network], [Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |
None |
5 |
Machine Learning Detected a DNS Request With a High DGA Probability Score |
A supervised machine learning model has identified a DNS question name with a high probability of sourcing from a Domain Generation Algorithm (DGA), which could indicate command and control network activity. |
[Domain: Network], [Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |
None |
5 |
Machine Learning Detected a Suspicious Windows Event with a High Malicious Probability Score |
A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model’s blocklist identified the event as being malicious. |
[OS: Windows], [Data Source: Elastic Endgame], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
10 |
Machine Learning Detected a Suspicious Windows Event with a Low Malicious Probability Score |
A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with low probability of it being malicious activity. Alternatively, the model’s blocklist identified the event as being malicious. |
[OS: Windows], [Data Source: Elastic Endgame], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
8 |
Elastic Endgame detected Malware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame] |
None |
103 |
|
Elastic Endgame prevented Malware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame] |
None |
103 |
|
This rules identifies a process created from an executable with a space appended to the end of the filename. This may indicate an attempt to masquerade a malicious file as benign to gain user execution. When a space is added to the end of certain files, the OS will execute the file according to it’s true filetype instead of it’s extension. Adversaries can hide a program’s true filetype by changing the extension of the file. They can then add a space to the end of the name so that the OS automatically executes the file when it’s double-clicked. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
7 |
|
A member was removed or their invitation to join was removed from a GitHub Organization. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
|
Identifies the creation of a memory dump file with an unusual extension, which can indicate an attempt to disguise a memory dump as another file type to bypass security defenses. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
2 |
|
This rule detects memory swap modification events on Linux systems. Memory swap modification can be used to manipulate the system’s memory and potentially impact the system’s performance. This behavior is commonly observed in malware that deploys miner software such as XMRig. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
1 |
|
This rule detects the creation of potentially malicious files within the default MOTD file directories. Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" directory. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
12 |
|
Identifies the deletion of an anti-phishing policy in Microsoft 365. By default, Microsoft 365 includes built-in features that help protect users from phishing attacks. Anti-phishing polices increase this protection by refining settings to better detect and prevent attacks. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |
None |
206 |
|
Identifies the modification of an anti-phishing rule in Microsoft 365. By default, Microsoft 365 includes built-in features that help protect users from phishing attacks. Anti-phishing rules increase this protection by refining settings to better detect and prevent attacks. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |
None |
206 |
|
Identifies when a DomainKeys Identified Mail (DKIM) signing configuration is disabled in Microsoft 365. With DKIM in Microsoft 365, messages that are sent from Exchange Online will be cryptographically signed. This will allow the receiving email system to validate that the messages were generated by a server that the organization authorized and were not spoofed. |
[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Persistence] |
None |
206 |
|
Identifies when a Data Loss Prevention (DLP) policy is removed in Microsoft 365. An adversary may remove a DLP policy to evade existing DLP monitoring. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies when a malware filter policy has been deleted in Microsoft 365. A malware filter policy is used to alert administrators that an internal user sent a message that contained malware. This may indicate an account or machine compromise that would need to be investigated. Deletion of a malware filter policy may be done to evade detection. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies when a malware filter rule has been deleted or disabled in Microsoft 365. An adversary or insider threat may want to modify a malware filter rule to evade detection. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies when a new role is assigned to a management group in Microsoft 365. An adversary may attempt to add a role in order to maintain persistence in an environment. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
206 |
|
Identifies when a safe attachment rule is disabled in Microsoft 365. Safe attachment rules can extend malware protections to include routing all messages and attachments without a known malware signature to a special hypervisor environment. An adversary or insider threat may disable a safe attachment rule to exfiltrate data or evade defenses. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies when a Safe Link policy is disabled in Microsoft 365. Safe Link policies for Office applications extend phishing protection to documents that contain hyperlinks, even after they have been delivered to a user. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |
None |
206 |
|
Identifies a transport rule creation in Microsoft 365. As a best practice, Exchange Online mail transport rules should not be set to forward email to domains outside of your organization. An adversary may create transport rules to exfiltrate data. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Exfiltration] |
None |
206 |
|
Identifies when a transport rule has been disabled or deleted in Microsoft 365. Mail flow rules (also known as transport rules) are used to identify and take action on messages that flow through your organization. An adversary or insider threat may modify a transport rule to exfiltrate data or evade defenses. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Exfiltration] |
None |
206 |
|
In Azure Active Directory (Azure AD), permissions to manage resources are assigned using roles. The Global Administrator is a role that enables users to have access to all administrative features in Azure AD and services that use Azure AD identities like the Microsoft 365 Defender portal, the Microsoft 365 compliance center, Exchange, SharePoint Online, and Skype for Business Online. Attackers can add users as Global Administrators to maintain access and manage all subscriptions and their settings and resources. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Persistence] |
None |
206 |
|
Identifies when a new Inbox forwarding rule is created in Microsoft 365. Inbox rules process messages in the Inbox based on conditions and take actions. In this case, the rules will forward the emails to a defined address. Attackers can abuse Inbox Rules to intercept and exfiltrate email data without making organization-wide configuration changes or having the corresponding privileges. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Collection] |
None |
206 |
|
Detects successful Microsoft 365 portal logins from rare locations. Rare locations are defined as locations that are not commonly associated with the user’s account. This behavior may indicate an adversary attempting to access a Microsoft 365 account from an unusual location or behind a VPN. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Threat Detection], [Tactic: Initial Access] |
None |
2 |
|
Microsoft 365 Portal Logins from Impossible Travel Locations |
Detects successful Microsoft 365 portal logins from impossible travel locations. Impossible travel locations are defined as two different countries within a short time frame. This behavior may indicate an adversary attempting to access a Microsoft 365 account from a compromised account or a malicious actor attempting to access a Microsoft 365 account from a different location. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Threat Detection], [Tactic: Initial Access] |
None |
2 |
Identifies when Microsoft Cloud App Security reports that a user has uploaded files to the cloud that might be infected with ransomware. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Impact] |
None |
206 |
|
Identifies when custom applications are allowed in Microsoft Teams. If an organization requires applications other than those available in the Teams app store, custom applications can be developed as packages and uploaded. An adversary may abuse this behavior to establish persistence in an environment. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |
None |
207 |
|
Identifies when external access is enabled in Microsoft Teams. External access lets Teams and Skype for Business users communicate with other users that are outside their organization. An adversary may enable external access or add an allowed domain to exfiltrate data or maintain persistence in an environment. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |
None |
206 |
|
Identifies when guest access is enabled in Microsoft Teams. Guest access in Teams allows people outside the organization to access teams and channels. An adversary may enable guest access to maintain persistence in an environment. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |
None |
206 |
|
Identifies that a user has deleted an unusually large volume of files as reported by Microsoft Cloud App Security. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Impact] |
None |
206 |
|
Identifies when a user has been restricted from sending email due to exceeding sending limits of the service policies per the Security Compliance Center. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |
None |
206 |
|
An instance of MSBuild, the Microsoft Build Engine, started a PowerShell script or the Visual C# Command Line Compiler. This technique is sometimes used to deploy a malicious payload using the Build Engine. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: System] |
None |
214 |
|
An instance of MSBuild, the Microsoft Build Engine, was started by a script or the Windows command interpreter. This behavior is unusual and is sometimes used by malicious payloads. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
211 |
|
An instance of MSBuild, the Microsoft Build Engine, was started by Explorer or the WMI (Windows Management Instrumentation) subsystem. This behavior is unusual and is sometimes used by malicious payloads. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
An instance of MSBuild, the Microsoft Build Engine, was started by Excel or Word. This is unusual behavior for the Build Engine and could have been caused by an Excel or Word document executing a malicious script payload. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
An instance of MSBuild, the Microsoft Build Engine, was started after being renamed. This is uncommon behavior and may indicate an attempt to run unnoticed or undetected. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
113 |
|
Identifies suspicious processes being spawned by the Microsoft Exchange Server Unified Messaging (UM) service. This activity has been observed exploiting CVE-2021-26857. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies suspicious files being written by the Microsoft Exchange Server Unified Messaging (UM) service. This activity has been observed exploiting CVE-2021-26858. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
208 |
|
Identifies the use of Cmdlets and methods related to Microsoft Exchange Transport Agents install. Adversaries may leverage malicious Microsoft Exchange Transport Agents to execute tasks in response to adversary-defined criteria, establishing persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: PowerShell Logs], [Rule Type: BBR] |
None |
7 |
|
Identifies suspicious processes being spawned by the Microsoft Exchange Server worker process (w3wp). This activity may indicate exploitation activity or access to an existing web shell backdoor. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Identifies use of aspnet_regiis to decrypt Microsoft IIS connection strings. An attacker with Microsoft IIS web server access via a webshell or alike can decrypt and dump any hardcoded connection strings, such as the MSSQL service account password using aspnet_regiis command. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies the Internet Information Services (IIS) command-line tool, AppCmd, being used to list passwords. An attacker with IIS web server access via a web shell can decrypt and dump the IIS AppPool service account password using AppCmd. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: System] |
None |
114 |
|
Identifies attempts to open a Microsoft Management Console File from untrusted paths. Adversaries may use MSC files for initial access and execution. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
8.13.0 |
206 |
|
Identifies when one or more features on Microsoft Defender are disabled. Adversaries may disable or tamper with Microsoft Defender features to evade detection and conceal malicious behavior. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Elastic Endgame] |
8.13.0 |
214 |
|
Identifies the password log file from the default Mimikatz memssp module. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
312 |
|
Identifies modifications of the AmsiEnable registry key to 0, which disables the Antimalware Scan Interface (AMSI). An adversary can modify this key to disable AMSI protections. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies use of bcdedit.exe to delete boot configuration data. This tactic is sometimes used as by malware or an attacker as a destructive technique. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies modification of the dynamic linker preload shared object (ld.so.preload). Adversaries may execute malicious payloads by hijacking the dynamic linker used to load libraries. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
209 |
|
Modification of Dynamic Linker Preload Shared Object Inside A Container |
This rule detects the creation or modification of the dynamic linker preload shared object (ld.so.preload) inside a container. The Linux dynamic linker is used to load libraries needed by a program at runtime. Adversaries may hijack the dynamic linker by modifying the /etc/ld.so.preload file to point to malicious libraries. This behavior can be used to grant unauthorized access to system resources and has been used to evade detection of malicious processes in container environments. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [Tactic: Defense Evasion] |
None |
1 |
Modification of Environment Variable via Unsigned or Untrusted Parent |
Identifies modifications to an environment variable using the built-in launchctl command. Adversaries may execute their own malicious payloads by hijacking certain environment variables to load arbitrary libraries or bypass certain restrictions. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
206 |
Adversaries may modify SSH related binaries for persistence or credential access by patching sensitive functions to enable unauthorized access or by logging SSH credentials for exfiltration. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
110 |
|
Identifies changes to the Safari configuration using the built-in defaults command. Adversaries may attempt to enable or disable certain Safari settings, such as enabling JavaScript from Apple Events to ease in the hijacking of the users browser. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
106 |
|
Modification of Standard Authentication Module or Configuration |
Adversaries may modify the standard authentication module for persistence via patching the normal authorization process or modifying the login configuration to allow unauthorized access or elevate privileges. |
[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
204 |
Identifies attempts to modify the WDigest security provider in the registry to force the user’s password to be stored in clear text in memory. This behavior can be indicative of an adversary attempting to weaken the security configuration of an endpoint. Once the UseLogonCredential value is modified, the adversary may attempt to dump clear text passwords from memory. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
111 |
|
Identify the modification of the msPKIAccountCredentials attribute in an Active Directory User Object. Attackers can abuse the credentials roaming feature to overwrite an arbitrary file for privilege escalation. ms-PKI-AccountCredentials contains binary large objects (BLOBs) of encrypted credential objects from the credential manager store, private keys, certificates, and certificate requests. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Data Source: Active Directory], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
13 |
|
Modification or Removal of an Okta Application Sign-On Policy |
Detects attempts to modify or delete a sign on policy for an Okta application. An adversary may attempt to modify or delete the sign on policy for an Okta application in order to remove or weaken an organization’s security controls. |
[Tactic: Persistence], [Use Case: Identity and Access Audit], [Data Source: Okta] |
None |
209 |
Managed Object Format (MOF) files can be compiled locally or remotely through mofcomp.exe. Attackers may leverage MOF files to build their own namespaces and classes into the Windows Management Instrumentation (WMI) repository, or establish persistence using WMI Event Subscription. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: Elastic Endgame], [Data Source: System], [Data Source: Crowdstrike] |
None |
4 |
|
This rule detects the use of the mount utility from inside a privileged container. The mount command is used to make a device or file system accessible to the system, and then to connect its root directory to a specified mount point on the local file system. When launched inside a privileged container—a container deployed with all the capabilities of the host machine-- an attacker can access sensitive host level files which could be used for further privilege escalation and container escapes to the host machine. Any usage of mount inside a running privileged container should be further investigated. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
1 |
|
Identifies the use of net.exe to mount a WebDav or hidden remote share. This may indicate lateral movement or preparation for data exfiltration. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies MsBuild.exe making outbound network connections. This may indicate adversarial activity as MsBuild is often leveraged by adversaries to execute code and evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
110 |
|
Identifies Mshta.exe making outbound network connections. This may indicate adversarial activity, as Mshta is often leveraged by adversaries to execute malicious scripts and evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Identifies the execution of an MsiExec service child process followed by network or dns lookup activity. Adversaries may abuse Windows Installers for initial access and delivery of malware. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
101 |
|
Identifies when multi-factor authentication (MFA) is disabled for an Azure user account. An adversary may disable MFA for a user account in order to weaken the authentication requirements for the account. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |
None |
105 |
|
This rule uses alert data to determine when multiple different alerts involving the same user are triggered. Analysts can use this to prioritize triage and response, as these users are more likely to be compromised. |
[Use Case: Threat Detection], [Rule Type: Higher-Order Rule] |
None |
3 |
|
Multiple Alerts in Different ATT&CK Tactics on a Single Host |
This rule uses alert data to determine when multiple alerts in different phases of an attack involving the same host are triggered. Analysts can use this to prioritize triage and response, as these hosts are more likely to be compromised. |
[Use Case: Threat Detection], [Rule Type: Higher-Order Rule] |
None |
4 |
This rule detects when a specific Okta actor has multiple device token hashes for a single Okta session. This may indicate an authenticated session has been hijacked or is being used by multiple devices. Adversaries may hijack a session to gain unauthorized access to Okta admin console, applications, tenants, or other resources. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Credential Access], [Domain: SaaS] |
8.13.0 |
104 |
|
Identifies multiple logon failures followed by a successful one from the same source address. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: System] |
None |
11 |
|
Identifies multiple consecutive logon failures from the same source address and within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: System] |
None |
10 |
|
Detects when a user has started multiple Okta sessions with the same user account and different session IDs. This may indicate that an attacker has stolen the user’s session cookie and is using it to access the user’s account from a different location. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Lateral Movement] |
None |
5 |
|
Multiple Okta User Auth Events with Same Device Token Hash Behind a Proxy |
Detects when Okta user authentication events are reported for multiple users with the same device token hash behind a proxy. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Credential Access] |
None |
5 |
Multiple Okta User Authentication Events with Client Address |
Detects when a certain threshold of Okta user authentication events are reported for multiple users from the same client address. Adversaries may attempt to launch a credential stuffing or password spraying attack from the same device by using a list of known usernames and passwords to gain unauthorized access to user accounts. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Credential Access] |
8.13.0 |
3 |
Multiple Okta User Authentication Events with Same Device Token Hash |
Detects when a high number of Okta user authentication events are reported for multiple users in a short time frame. Adversaries may attempt to launch a credential stuffing or password spraying attack from the same device by using a list of known usernames and passwords to gain unauthorized access to user accounts. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Credential Access] |
8.13.0 |
3 |
Windows Credential Manager allows you to create, view, or delete saved credentials for signing into websites, connected applications, and networks. An adversary may abuse this to list or dump credentials stored in the Credential Manager for saved usernames and passwords. This may also be performed in preparation of lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: System] |
None |
11 |
|
This rule helps you test and practice using alerts with Elastic Security as you get set up. It’s not a sign of threat activity. |
[Use Case: Guided Onboarding] |
None |
3 |
|
Identifies the execution of wbadmin to access the NTDS.dit file in a domain controller. Attackers with privileges from groups like Backup Operators can abuse the utility to perform credential access and compromise the domain. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
102 |
|
Identifies a copy operation of the Active Directory Domain Database (ntds.dit) or Security Account Manager (SAM) files. Those files contain sensitive information including hashed domain and/or local credentials. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Sysmon] |
8.13.0 |
214 |
|
Identifies suspicious usage of unshare to manipulate system namespaces. Unshare can be utilized to escalate privileges or escape container security boundaries. Threat actors have utilized this binary to allow themselves to escape to the host and access other resources or escalate privileges. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
9 |
|
This rule detects an established netcat listener running inside a container. Netcat is a utility used for reading and writing data across network connections, and it can be used for malicious purposes such as establishing a backdoor for persistence or exfiltrating data. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |
None |
2 |
|
Monitors for the execution of a netcat listener via rlwrap. rlwrap is a readline wrapper, a small utility that uses the GNU Readline library to allow the editing of keyboard input for any command. This utility can be used in conjunction with netcat to gain a more stable reverse shell. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
3 |
|
Identifies the addition of a Netsh Helper DLL, netsh.exe supports the addition of these DLLs to extend its functionality. Attackers may abuse this mechanism to execute malicious payloads every time the utility is executed, which can be done by administrators or a scheduled task. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Sysmon] |
8.13.0 |
102 |
|
This rule monitors for network connections from a kworker process. kworker, or kernel worker, processes are part of the kernel’s workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
6 |
|
This rule monitors for the execution of the cat command, followed by a connection attempt by the same process. Cat is capable of transfering data via tcp/udp channels by redirecting its read output to a /dev/tcp or /dev/udp channel. This activity is highly suspicious, and should be investigated. Attackers may leverage this capability to transfer tools or files to another host in the network or exfiltrate data while attempting to evade detection in the process. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
6 |
|
This rule identifies an egress internet connection initiated by an SSH Daemon child process. This behavior is indicative of the alteration of a shell configuration file or other mechanism that launches a process when a new SSH login occurs. Attackers can also backdoor the SSH daemon to allow for persistence, call out to a C2 or to steal credentials. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
3 |
|
This detection rule addresses multiple vulnerabilities in the CUPS printing system, including CVE-2024-47176, CVE-2024-47076, CVE-2024-47175, and CVE-2024-47177. Specifically, this rule detects network connections initiated by a child processes of foomatic-rip. These flaws impact components like cups-browsed, libcupsfilters, libppd, and foomatic-rip, allowing remote unauthenticated attackers to manipulate IPP URLs or inject malicious data through crafted UDP packets or network spoofing. This can result in arbitrary command execution when a print job is initiated. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Use Case: Vulnerability], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
1 |
|
Monitors for the execution of a unix binary with read, write and execute memory region permissions, followed by a network connection. The mprotect() system call is used to change the access protections on a region of memory that has already been allocated. This syscall allows a process to modify the permissions of pages in its virtual address space, enabling or disabling permissions such as read, write, and execute for those pages. RWX permissions on memory is in many cases overly permissive, and should (especially in conjunction with an outbound network connection) be analyzed thoroughly. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
3 |
|
Identifies certutil.exe making a network connection. Adversaries could abuse certutil.exe to download a certificate, or malware, from a remote URL. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Elastic Endgame], [Rule Type: BBR] |
None |
115 |
|
Compiled HTML files (.chm) are commonly distributed as part of the Microsoft HTML Help system. Adversaries may conceal malicious code in a CHM file and deliver it to a victim for execution. CHM content is loaded by the HTML Help executable program (hh.exe). |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Identifies msxsl.exe making a network connection. This may indicate adversarial activity as msxsl.exe is often leveraged by adversaries to execute malicious scripts and evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
106 |
|
This rule monitors a sequence involving a program compilation event followed by its execution and a subsequent network connection event. This behavior can indicate the set up of a reverse tcp connection to a command-and-control server. Attackers may spawn reverse shells to establish persistence onto a target system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
6 |
|
Identifies the native Windows tools regsvr32.exe, regsvr64.exe, RegSvcs.exe, or RegAsm.exe making a network connection. This may be indicative of an attacker bypassing allowlists or running arbitrary scripts via a signed Microsoft binary. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Binaries signed with trusted digital certificates can execute on Windows systems protected by digital signature validation. Adversaries may use these binaries to live off the land and execute malicious files that could bypass application allowlists and signature validation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Detects network connections initiated by the "sudo" binary. This behavior is uncommon and may occur in instances where reverse shell shellcode is injected into a process run with elevated permissions via "sudo". Attackers may attempt to inject shellcode into processes running as root, to escalate privileges. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
3 |
|
Detects network connections initiated through Cross-Desktop Group (XDG) autostart entries for GNOME and XFCE-based Linux distributions. XDG Autostart entries can be used to execute arbitrary commands or scripts when a user logs in. This rule helps to identify potential malicious activity where an attacker may have modified XDG autostart scripts to establish persistence on the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies the modification of the network logon provider registry. Adversaries may register a rogue network logon provider module for persistence and/or credential access via intercepting the authentication credentials in clear text during user logon. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
113 |
|
Identifies the ability of a process to be able to create RAW and PACKET socket types for the available network namespaces by a non-root user. A malicious process with this capability may exploit routing between hosts, bypass network access controls, and otherwise tamper with host networking if a firewall is not in place to limit the packet types and contents. The CAP_NET_RAW capability allows the process to bind to any address within the available namespaces, which allows network traffic sniffing by a non root user. The rule identifies previously unknown processes executing with CAP_NET_RAW capabilities through the use of the new terms rule type. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
4 |
|
A machine learning job detected a rare destination country name in the network logs. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from a server in a country which does not normally appear in network traffic or business work-flows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network. |
[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |
None |
104 |
|
Identifies the attempt to disable Network-Level Authentication (NLA) via registry modification. Network Level Authentication (NLA) is a feature on Windows that provides an extra layer of security for Remote Desktop (RDP) connections, as it requires users to authenticate before allowing a full RDP session. Attackers can disable NLA to enable persistence methods that require access to the Windows sign-in screen without authenticating, such as Accessibility Features persistence methods, like Sticky Keys. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Sysmon] |
8.13.0 |
103 |
|
Identifies the use of the Exchange PowerShell cmdlet, Set-CASMailbox, to add a new ActiveSync allowed device. Adversaries may target user email to collect sensitive information. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
This rule detects when a new GitHub App has been installed in your organization account. GitHub Apps extend GitHub’s functionality both within and outside of GitHub. When an app is installed it is granted permissions to read or modify your repository and organization data. Only trusted apps should be installed and any newly installed apps should be investigated to verify their legitimacy. Unauthorized app installation could lower your organization’s security posture and leave you exposed for future attacks. |
[Domain: Cloud], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Github] |
8.12.0 |
103 |
|
Detects when a new member is added to a GitHub organization as an owner. This role provides admin level privileges. Any new owner roles should be investigated to determine it’s validity. Unauthorized owner roles could indicate compromise within your organization and provide unlimited access to data and settings. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Data Source: Github] |
8.12.0 |
105 |
|
Detects events where Okta behavior detection has identified a new authentication behavior. |
[Use Case: Identity and Access Audit], [Tactic: Initial Access], [Data Source: Okta] |
None |
5 |
|
Detects the creation of a new Identity Provider (IdP) by a Super Administrator or Organization Administrator within Okta. |
[Use Case: Identity and Access Audit], [Tactic: Persistence], [Data Source: Okta] |
None |
4 |
|
A new user was added to a GitHub organization. |
[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Github] |
8.12.0 |
103 |
|
Identifies a new or modified federation domain, which can be used to create a trust between O365 and an external identity provider. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |
None |
207 |
|
Nping ran on a Linux host. Nping is part of the Nmap tool suite and has the ability to construct raw packets for a wide variety of security testing applications, including denial of service testing. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
108 |
|
Identifies NullSessionPipe registry modifications that specify which pipes can be accessed anonymously. This could be indicative of adversary lateral movement preparation by making the added pipe available to everyone. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Detects the occurrence of emails reported as Phishing or Malware by Users. Security Awareness training is essential to stay ahead of scammers and threat actors, as security products can be bypassed, and the user can still receive a malicious message. Educating users to report suspicious messages can help identify gaps in security controls and prevent malware infections and Business Email Compromise attacks. |
[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Initial Access] |
None |
206 |
|
Identifies accounts with a high number of single sign-on (SSO) logon errors. Excessive logon errors may indicate an attempt to brute force a password or SSO token. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |
None |
207 |
|
Identifies the assignment of rights to access content from another mailbox. An adversary may use the compromised account to send messages to other accounts in the network of the target organization while creating inbox rules, so messages can evade spam/phishing detection mechanisms. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |
None |
206 |
|
Detects the occurrence of mailbox audit bypass associations. The mailbox audit is responsible for logging specified mailbox events (like accessing a folder or a message or permanently deleting a message). However, actions taken by some authorized accounts, such as accounts used by third-party tools or accounts used for lawful monitoring, can create a large number of mailbox audit log entries and may not be of interest to your organization. Because of this, administrators can create bypass associations, allowing certain accounts to perform their tasks without being logged. Attackers can abuse this allowlist mechanism to conceal actions taken, as the mailbox audit will log no activity done by the account. |
[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Initial Access], [Tactic: Defense Evasion] |
None |
206 |
|
Identifies the modification of the Microsoft Office "Office Test" Registry key, a registry location that can be used to specify a DLL which will be executed every time an MS Office application is started. Attackers can abuse this to gain persistence on a compromised host. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
103 |
|
Identifies a high number of failed Okta user authentication attempts from a single IP address, which could be indicative of a brute force or password spraying attack. An adversary may attempt a brute force or password spraying attack to obtain unauthorized access to user accounts. |
[Use Case: Identity and Access Audit], [Tactic: Credential Access], [Data Source: Okta] |
None |
211 |
|
Detects when Okta FastPass prevents a user from authenticating to a phishing website. |
[Tactic: Initial Access], [Use Case: Identity and Access Audit], [Data Source: Okta] |
None |
106 |
|
Detects sign-in events where authentication is carried out via a third-party Identity Provider (IdP). |
[Use Case: Identity and Access Audit], [Tactic: Initial Access], [Data Source: Okta] |
None |
5 |
|
Okta ThreatInsight is a feature that provides valuable debug data regarding authentication and authorization processes, which is logged in the system. Within this data, there is a specific field called threat_suspected, which represents Okta’s internal evaluation of the authentication or authorization workflow. When this field is set to True, it suggests the presence of potential credential access techniques, such as password-spraying, brute-forcing, replay attacks, and other similar threats. |
[Use Case: Identity and Access Audit], [Data Source: Okta] |
None |
208 |
|
A user has initiated a session impersonation granting them access to the environment with the permissions of the user they are impersonating. This would likely indicate Okta administrative access and should only ever occur if requested and expected. |
[Use Case: Identity and Access Audit], [Tactic: Credential Access], [Data Source: Okta] |
None |
210 |
|
Detects when a specific Okta actor has multiple sessions started from different geolocations. Adversaries may attempt to launch an attack by using a list of known usernames and passwords to gain unauthorized access to user accounts from different locations. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Initial Access] |
8.13.0 |
103 |
|
Identifies the occurence of files uploaded to OneDrive being detected as Malware by the file scanning engine. Attackers can use File Sharing and Organization Repositories to spread laterally within the company and amplify their access. Users can inadvertently share these files without knowing their maliciousness, giving adversaries opportunity to gain initial access to other endpoints in the environment. |
[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Lateral Movement] |
None |
206 |
|
This rule identifies when the openssl client or server is used to establish a connection. Attackers may use openssl to establish a secure connection to a remote server or to create a secure server to receive connections. This activity may be used to exfiltrate data or establish a command and control channel. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
2 |
|
Identifies the PowerShell process loading the Task Scheduler COM DLL followed by an outbound RPC network connection within a short time period. This may indicate lateral movement or remote discovery via scheduled tasks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
109 |
|
Identifies modifications in registry keys associated with abuse of the Outlook Home Page functionality for command and control or persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
101 |
|
Identifies parent process spoofing used to thwart detection. Adversaries may spoof the parent process identifier (PPID) of a new process to evade process-monitoring defenses or to elevate privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies use of the Windows file system utility (fsutil.exe) to gather information about attached peripheral devices and components connected to a computer system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Elastic Endgame detected Permission Theft. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
103 |
|
Elastic Endgame prevented Permission Theft. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
103 |
|
An adversary can use the Background Intelligent Transfer Service (BITS) SetNotifyCmdLine method to execute a program that runs after a job finishes transferring data or after a job enters a specified state in order to persist on a system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
310 |
|
Identifies the creation or modification of a DirectoryService PlugIns (dsplug) file. The DirectoryService daemon launches on each system boot and automatically reloads after crash. It scans and executes bundles that are located in the DirectoryServices PlugIns folder and can be abused by adversaries to maintain persistence. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
106 |
|
An adversary can establish persistence by modifying an existing macOS dock property list in order to execute a malicious application instead of the intended one when invoked. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
107 |
|
Detects modification of a Folder Action script. A Folder Action script is executed when the folder to which it is attached has items added or removed, or when its window is opened, closed, moved, or resized. Adversaries may abuse this feature to establish persistence by utilizing a malicious script. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies a persistence mechanism that utilizes the NtSetValueKey native API to create a hidden (null terminated) registry key. An adversary may use this method to hide from system utilities such as the Registry Editor (regedit). |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
109 |
|
Persistence via KDE AutoStart Script or Desktop File Modification |
Identifies the creation or modification of a K Desktop Environment (KDE) AutoStart script or desktop file that will execute upon each user logon. Adversaries may abuse this method for persistence. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
114 |
Identifies use of the Defaults command to install a login or logoff hook in MacOS. An adversary may abuse this capability to establish persistence in an environment by inserting code to be executed at login or logout. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
107 |
|
Detects attempts to establish persistence on an endpoint by abusing Microsoft Office add-ins. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
208 |
|
Detects attempts to establish persistence on an endpoint by installing a rogue Microsoft Outlook VBA Template. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
207 |
|
Identifies the creation or modification of a PowerShell profile. PowerShell profile is a script that is executed when PowerShell starts to customize the user environment, which can be abused by attackers to persist in a environment where PowerShell is common. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
109 |
|
A job can be used to schedule programs or scripts to be executed at a specified date and time. Adversaries may abuse task scheduling functionality to facilitate initial or recurring execution of malicious code. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
311 |
|
Detects the successful hijack of Microsoft Compatibility Appraiser scheduled task to establish persistence with an integrity level of system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies potential hijacking of the Microsoft Update Orchestrator Service to establish persistence with an integrity level of SYSTEM. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
An adversary can use Windows Management Instrumentation (WMI) to install event filters, providers, consumers, and bindings that execute code when a defined event occurs. Adversaries may use the capabilities of WMI to subscribe to an event and execute arbitrary code when that event occurs, providing persistence on a system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies use of the Windows Management Instrumentation StdRegProv (registry provider) to modify commonly abused registry locations for persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
109 |
|
Identifies when the Windows installer process msiexec.exe creates a new persistence entry via scheduled tasks or startup. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies script engines creating files in the Startup folder, or the creation of script files in the Startup folder. Adversaries may abuse this technique to maintain persistence in an environment. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies the creation of a new port forwarding rule. An adversary may abuse this technique to bypass network segmentation restrictions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
313 |
|
Possible Consent Grant Attack via Azure-Registered Application |
Detects when a user grants permissions to an Azure-registered application or when an administrator grants tenant-wide permissions to an application. An adversary may create an Azure-registered application that requests access to data such as contact information, email, or documents. |
[Domain: Cloud], [Data Source: Azure], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |
None |
212 |
This rule detects a known command and control pattern in network events. The FIN7 threat group is known to use this command and control technique, while maintaining persistence in their target’s network. |
[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint], [Data Source: PAN-OS] |
None |
106 |
|
Detects possible Denial of Service (DoS) attacks against an Okta organization. An adversary may attempt to disrupt an organization’s business operations by performing a DoS attack against its Okta service. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Impact] |
None |
208 |
|
Active Directory Integrated DNS (ADIDNS) is one of the core components of AD DS, leveraging AD’s access control and replication to maintain domain consistency. It stores DNS zones as AD objects, a feature that, while robust, introduces some security issues, such as wildcard records, mainly because of the default permission (Any authenticated users) to create DNS-named records. Attackers can create wildcard records to redirect traffic that doesn’t explicitly match records contained in the zone, becoming the Man-in-the-Middle and being able to abuse DNS similarly to LLMNR/NBNS spoofing. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
3 |
|
Identifies potential ransomware note being uploaded to an AWS S3 bucket. This rule detects the |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS S3], [Use Case: Threat Detection], [Tactic: Impact] |
8.13.0 |
3 |
|
Potential Abuse of Resources by High Token Count and Large Response Sizes |
Detects potential resource exhaustion or data breach attempts by monitoring for users who consistently generate high input token counts, submit numerous requests, and receive large responses. This behavior could indicate an attempt to overload the system or extract an unusually large amount of data, possibly revealing sensitive information or causing service disruptions. |
[Domain: LLM], [Data Source: AWS Bedrock], [Data Source: Amazon Web Services], [Data Source: AWS S3], [Use Case: Potential Overload], [Use Case: Resource Exhaustion], [Mitre Atlas: LLM04] |
8.13.0 |
3 |
Identifies the modification of the nTSecurityDescriptor attribute in a domain object with rights related to DCSync to a user/computer account. Attackers can use this backdoor to re-obtain access to hashes of any user/computer. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
4 |
|
Identifies attempts to add an account to the admin group via the command line. This could be an indication of privilege escalation activity. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
206 |
|
Identifies the execution of PowerShell script with keywords related to different Antimalware Scan Interface (AMSI) bypasses. An adversary may attempt first to disable AMSI before executing further malicious powershell scripts to evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |
None |
10 |
|
The Application Shim was created to allow for backward compatibility of software as the operating system codebase changes over time. This Windows functionality has been abused by attackers to stealthily gain persistence and arbitrary code execution in legitimate Windows processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Detects potential buffer overflow attacks by querying the "Segfault Detected" pre-built rule signal index, through a threshold rule, with a minimum number of 100 segfault alerts in a short timespan. A large amount of segfaults in a short time interval could indicate application exploitation attempts. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Initial Access], [Use Case: Vulnerability], [Rule Type: Higher-Order Rule] |
None |
3 |
|
Monitors for the execution of a file system mount followed by a chroot execution. Given enough permissions, a user within a container is capable of mounting the root file system of the host, and leveraging chroot to escape its containarized environment. This behavior pattern is very uncommon and should be investigated. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Domain: Container], [Data Source: Elastic Defend] |
None |
2 |
|
This rule monitors for suspicious activities that may indicate an attacker attempting to execute arbitrary code within a PostgreSQL environment. Attackers can execute code via PostgreSQL as a result of gaining unauthorized access to a public facing PostgreSQL database or exploiting vulnerabilities, such as remote command execution and SQL injection attacks, which can result in unauthorized access and malicious actions, and facilitate post-exploitation activities for unauthorized access and malicious actions. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
7 |
|
Identifies instances of Internet Explorer (iexplore.exe) being started via the Component Object Model (COM) making unusual network connections. Adversaries could abuse Internet Explorer via COM to avoid suspicious processes making network connections and bypass host-based firewall restrictions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
106 |
|
Potential Container Escape via Modified notify_on_release File |
This rule detects modification of the cgroup notify_on_release file from inside a container. When the notify_on_release flag is enabled (1) in a cgroup, then whenever the last task in the cgroup exits or attaches to another cgroup, the command specified in the release_agent file is run and invoked from the host. A privileged container with SYS_ADMIN capabilities, enables a threat actor to mount a cgroup directory and modify the notify_on_release flag in order to take advantage of this feature, which could be used for further privilege escalation and container escapes to the host machine. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
1 |
This rule detects modification of the CGroup release_agent file from inside a privileged container. The release_agent is a script that is executed at the termination of any process on that CGroup and is invoked from the host. A privileged container with SYS_ADMIN capabilities, enables a threat actor to mount a CGroup directory and modify the release_agent which could be used for further privilege escalation and container escapes to the host machine. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
1 |
|
Identifies the execution of a Chromium based browser with the debugging process argument, which may indicate an attempt to steal authentication cookies. An adversary may steal web application or service session cookies and use them to gain access web applications or Internet services as an authenticated user without needing credentials. |
[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
107 |
|
This rule identifies when a User Account starts the Active Directory Replication Process. Attackers can use the DCSync technique to get credential information of individual accounts or the entire domain, thus compromising the entire domain. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Privilege Escalation], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
115 |
|
Identifies suspicious access to an LSASS handle via DuplicateHandle from an unknown call trace module. This may indicate an attempt to bypass the NtOpenProcess API to evade detection and dump LSASS memory for credential access. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |
None |
208 |
|
Identifies suspicious access to LSASS handle from a call trace pointing to DBGHelp.dll or DBGCore.dll, which both export the MiniDumpWriteDump method that can be used to dump LSASS memory content in preparation for credential access. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic:Execution], [Data Source: Sysmon] |
None |
210 |
|
Identifies the creation or modification of a medium size memory dump file which can indicate an attempt to access credentials from a process memory. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
3 |
|
Identifies suspicious renamed COMSVCS.DLL Image Load, which exports the MiniDump function that can be used to dump a process memory. This may indicate an attempt to dump LSASS memory while bypassing command-line based detection in preparation for credential access. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Sysmon] |
None |
108 |
|
An instance of MSBuild, the Microsoft Build Engine, loaded DLLs (dynamically linked libraries) responsible for Windows credential management. This technique is sometimes used for credential dumping. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
110 |
|
Identifies the execution of known Windows utilities often abused to dump LSASS memory or the Active Directory database (NTDS.dit) in preparation for credential access. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Sysmon] |
8.13.0 |
215 |
|
Cross-Site Scripting (XSS) is a type of attack in which malicious scripts are injected into trusted websites. In XSS attacks, an attacker uses a benign web application to send malicious code, generally in the form of a browser-side script. This detection rule identifies the potential malicious executions of such browser-side scripts. |
[Data Source: APM], [Use Case: Threat Detection], [Tactic: Initial Access], [Rule Type: BBR] |
None |
2 |
|
A population analysis machine learning job detected potential DGA (domain generation algorithm) activity. Such activity is often used by malware command and control (C2) channels. This machine learning job looks for a source IP address making DNS requests that have an aggregate high probability of being DGA activity. |
[Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |
None |
5 |
|
Potential DLL Side-Loading via Microsoft Antimalware Service Executable |
Identifies a Windows trusted program that is known to be vulnerable to DLL Search Order Hijacking starting after being renamed or from a non-standard path. This is uncommon behavior and may indicate an attempt to evade defenses via side-loading a malicious DLL within the memory space of one of those processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
111 |
Identifies an instance of a Windows trusted program that is known to be vulnerable to DLL Search Order Hijacking starting after being renamed or from a non-standard path. This is uncommon behavior and may indicate an attempt to evade defenses via side loading a malicious DLL within the memory space of one of those processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
111 |
|
This rule identifies a large number (15) of nslookup.exe executions with an explicit query type from the same host. This may indicate command and control activity utilizing the DNS protocol. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Sysmon] |
8.13.0 |
211 |
|
Potential Data Exfiltration Activity to an Unusual Destination Port |
A machine learning job has detected data exfiltration to a particular destination port. Data transfer patterns that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |
[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |
None |
4 |
Potential Data Exfiltration Activity to an Unusual IP Address |
A machine learning job has detected data exfiltration to a particular geo-location (by IP address). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |
[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |
None |
4 |
A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |
[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |
None |
4 |
|
A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |
[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |
None |
4 |
|
This rule looks for the usage of common data splitting utilities with specific arguments that indicate data splitting for exfiltration on Linux systems. Data splitting is a technique used by adversaries to split data into smaller parts to avoid detection and exfiltrate data. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Exfiltration], [Data Source: Elastic Defend] |
None |
1 |
|
The Microsoft Connection Manager Profile Installer (CMSTP.exe) is a command-line program to install Connection Manager service profiles, which accept installation information file (INF) files. Adversaries may abuse CMSTP to proxy the execution of malicious code by supplying INF files that contain malicious commands. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Sysmon], [Data Source: Elastic Endgame], [Data Source: System] |
None |
5 |
|
This rule detects the creation or rename of the Doas configuration file on a Linux system. Adversaries may create or modify the Doas configuration file to elevate privileges and execute commands as other users while attempting to evade detection. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
1 |
|
Identifies the execution of the PRoot utility, an open-source tool for user-space implementation of chroot, mount --bind, and binfmt_misc. Adversaries can leverage an open-source tool PRoot to expand the scope of their operations to multiple Linux distributions and simplify their necessary efforts. In a normal threat scenario, the scope of an attack is limited by the varying configurations of each Linux distribution. With PRoot, it provides an attacker with a consistent operational environment across different Linux distributions, such as Ubuntu, Fedora, and Alpine. PRoot also provides emulation capabilities that allow for malware built on other architectures, such as ARM, to be run.The post-exploitation technique called bring your own filesystem (BYOF), can be used by the threat actors to execute malicious payload or elevate privileges or perform network scans or orchestrate another attack on the environment. Although PRoot was originally not developed with malicious intent it can be easily tuned to work for one. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
7 |
|
This rule monitors for potential attempts to disable AppArmor. AppArmor is a Linux security module that enforces fine-grained access control policies to restrict the actions and resources that specific applications and processes can access. Adversaries may disable security tools to avoid possible detection of their tools and activities. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
7 |
|
Identifies potential attempts to disable Security-Enhanced Linux (SELinux), which is a Linux kernel security feature to support access control policies. Adversaries may disable security tools to avoid possible detection of their tools and activities. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
110 |
|
Identifies processes loading Active Directory related modules followed by a network connection to the ADWS dedicated TCP port. Adversaries may abuse the ADWS Windows service that allows Active Directory to be queried via this web service. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies when a browser process navigates to the Microsoft Help page followed by spawning an elevated process. This may indicate a successful exploitation for privilege escalation abusing a vulnerable Windows Installer repair setup. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
102 |
|
The Filter Manager Control Program (fltMC.exe) binary may be abused by adversaries to unload a filter driver and evade defenses. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
None |
113 |
|
Identifies multiple Windows Filtering Platform block events and where the process name is related to an endpoint security software. Adversaries may add malicious WFP rules to prevent Endpoint security from sending telemetry. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: System] |
None |
4 |
|
This rule detects the potential execution of the |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
2 |
|
It identifies potential malicious shell executions through remote SSH and detects cases where the sshd service suddenly terminates soon after successful execution, suggesting suspicious behavior similar to the XZ backdoor. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |
None |
4 |
|
Potential Exploitation of an Unquoted Service Path Vulnerability |
Adversaries may leverage unquoted service path vulnerabilities to escalate privileges. By placing an executable in a higher-level directory within the path of an unquoted service executable, Windows will natively launch this executable from its defined path variable instead of the benign one in a deeper directory, thus leading to code execution. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Elastic Endgame], [Data Source: Sysmon], [Data Source: System] |
8.13.0 |
103 |
Identifies multiple external consecutive login failures targeting a user account from the same source address within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to these accounts. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |
None |
7 |
|
Identifies the use of a browser to download a file from a remote URL and from a suspicious parent process. Adversaries may use browsers to avoid ingress tool transfer restrictions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Windows], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Sysmon] |
8.13.0 |
102 |
|
Identifies Certreq making an HTTP Post request. Adversaries could abuse Certreq to download files or upload data to a remote URL. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Command and Control], [Tactic: Exfiltration], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
109 |
|
Identifies the Foxmail client spawning a child process with argument pointing to the Foxmail temp directory. This may indicate the successful exploitation of a Foxmail vulnerability for initial access and execution via a malicious email. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: System], [Data Source: Elastic Endgame], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
101 |
|
This rule detects potential hex payload execution on Linux systems. Adversaries may use hex encoding to obfuscate payloads and evade detection mechanisms. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies attempts to create a local account that will be hidden from the macOS logon window. This may indicate an attempt to evade user attention while maintaining persistence using a separate local account. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies the execution of mount process with hidepid parameter, which can make processes invisible to other users from the system. Adversaries using Linux kernel version 3.2+ (or RHEL/CentOS v6.5+ above) can hide the process from other users. When hidepid=2 option is executed to mount the /proc filesystem, only the root user can see all processes and the logged-in user can only see their own process. This provides a defense evasion mechanism for the adversaries to hide their process executions from all other commands such as ps, top, pgrep and more. With the Linux kernel hardening hidepid option all the user has to do is remount the /proc filesystem with the option, which can now be monitored and detected. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
9 |
|
Identifies multiple internal consecutive login failures targeting a user account from the same source address within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to these accounts. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |
None |
11 |
|
Mimikatz is a credential dumper capable of obtaining plaintext Windows account logins and passwords, along with many other features that make it useful for testing the security of networks. This rule detects Invoke-Mimikatz PowerShell script and alike. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
110 |
|
Identifies an outbound network connection by JAVA to LDAP, RMI or DNS standard ports followed by a suspicious JAVA child processes. This may indicate an attempt to exploit a JAVA/NDI (Java Naming and Directory Interface) injection vulnerability. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
104 |
|
Identifies use of Bifrost, a known macOS Kerberos pentesting tool, which can be used to dump cached Kerberos tickets or attempt unauthorized authentication techniques such as pass-the-ticket/hash and kerberoasting. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |
None |
106 |
|
Adversaries can use the autostart mechanism provided by the Local Security Authority (LSA) authentication packages for privilege escalation or persistence by placing a reference to a binary in the Windows registry. The binary will then be executed by SYSTEM when the authentication packages are loaded. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint] |
None |
106 |
|
Identifies the creation of an LSASS process clone via PssCaptureSnapShot where the parent process is the initial LSASS process instance. This may indicate an attempt to evade detection and dump LSASS memory for credential access. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon], [Data Source: System] |
None |
108 |
|
Identifies suspicious access to an LSASS handle via PssCaptureSnapShot where two successive process accesses are performed by the same process and target two different instances of LSASS. This may indicate an attempt to evade detection and dump LSASS memory for credential access. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |
None |
210 |
|
Identifies the creation or change of a Windows executable file over network shares. Adversaries may transfer tools or other files between systems in a compromised environment. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
109 |
|
Identifies the attempt to create a new backdoor user by setting the user’s UID to 0. Attackers may alter a user’s UID to 0 to establish persistence on a system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
8 |
|
Identifies the execution of the mimipenguin exploit script which is linux adaptation of Windows tool mimikatz. Mimipenguin exploit script is used to dump clear text passwords from a currently logged-in user. The tool exploits a known vulnerability CVE-2018-20781. Malicious actors can exploit the cleartext credentials in memory by dumping the process and extracting lines that have a high probability of containing cleartext passwords. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
7 |
|
Identifies the execution of the unshadow utility which is part of John the Ripper, a password-cracking tool on the host machine. Malicious actors can use the utility to retrieve the combined contents of the /etc/shadow and /etc/password files. Using the combined file generated from the utility, the malicious threat actors can use them as input for password-cracking utilities or prepare themselves for future operations by gathering credential information of the victim. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
8 |
|
Monitors for the execution of different processes that might be used by attackers for malicious intent. An alert from this rule should be investigated further, as hack tools are commonly used by blue teamers and system administrators as well. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
4 |
|
Identifies multiple consecutive login attempts executed by one process targeting a local linux user account within a short time interval. Adversaries might brute force login attempts across different users with a default wordlist or a set of customly crafted passwords in an attempt to gain access to these accounts. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
7 |
|
This rule identifies a sequence of a mass file encryption event in conjunction with the creation of a .txt file with a file name containing ransomware keywords executed by the same process in a 1 second timespan. Ransomware is a type of malware that encrypts a victim’s files or systems and demands payment (usually in cryptocurrency) in exchange for the decryption key. One important indicator of a ransomware attack is the mass encryption of the file system, after which a new file extension is added to the file. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend] |
None |
10 |
|
This rule monitors for a set of Linux utilities that can be used for tunneling and port forwarding. Attackers can leverage tunneling and port forwarding techniques to bypass network defenses, establish hidden communication channels, and gain unauthorized access to internal resources, facilitating data exfiltration, lateral movement, and remote control. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
7 |
|
Identifies attempt to coerce a local NTLM authentication via HTTP using the Windows Printer Spooler service as a target. An adversary may use this primitive in combination with other techniques to elevate privileges on a compromised system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies suspicious instances of browser processes, such as unsigned or signed with unusual certificates, that can indicate an attempt to conceal malicious activity, bypass security features such as allowlists, or trick users into executing malware. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
5 |
|
Identifies executables with names resembling legitimate business applications but lacking signatures from the original developer. Attackers may trick users into downloading malicious executables that masquerade as legitimate applications via malicious ads, forum posts, and tutorials, effectively gaining initial access. |
[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Initial Access], [Tactic: Execution] |
None |
4 |
|
Identifies suspicious instances of communications apps, both unsigned and renamed ones, that can indicate an attempt to conceal malicious activity, bypass security features such as allowlists, or trick users into executing malware. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
6 |
|
Identifies suspicious instances of default system32 DLLs either unsigned or signed with non-MS certificates. This can potentially indicate the attempt to masquerade as system DLLs, perform DLL Search Order Hijacking or backdoor and resign legitimate DLLs. |
[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR] |
None |
105 |
|
Identifies suspicious instances of default system32 executables, either unsigned or signed with non-MS certificates. This could indicate the attempt to masquerade as system executables or backdoored and resigned legitimate executables. |
[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR] |
None |
5 |
|
Identifies instances of VLC-related DLLs which are not signed by the original developer. Attackers may name their payload as legitimate applications to blend into the environment, or embedding its malicious code within legitimate applications to deceive machine learning algorithms by incorporating authentic and benign code. |
[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR] |
None |
4 |
|
Monitors for the execution of Unix utilities that may be leveraged as memory address seekers. Attackers may leverage built-in utilities to seek specific memory addresses, allowing for potential future manipulation/exploitation. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
3 |
|
This detection rule identifies a sample of suspicious Linux system file reads used for system fingerprinting, leveraged by the Metasploit Meterpreter shell to gather information about the target that it is executing its shell on. Detecting this pattern is indicative of a successful meterpreter shell connection. |
[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |
None |
7 |
|
Identifies the creation of a suspicious zip file prepended with special characters. Sandboxed Microsoft Office applications on macOS are allowed to write files that start with special characters, which can be combined with an AutoStart location to achieve sandbox evasion. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
106 |
|
Windows contains accessibility features that may be launched with a key combination before a user has logged in. An adversary can modify the way these programs are launched to get a command prompt or backdoor without logging in to the system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
112 |
|
This rule identifies a potential port scan. A port scan is a method utilized by attackers to systematically scan a target system or network for open ports, allowing them to identify available services and potential vulnerabilities. By mapping out the open ports, attackers can gather critical information to plan and execute targeted attacks, gaining unauthorized access, compromising security, and potentially leading to data breaches, unauthorized control, or further exploitation of the targeted system or network. This rule proposes threshold logic to check for connection attempts from one source host to 20 or more destination ports. |
[Domain: Network], [Tactic: Discovery], [Tactic: Reconnaissance], [Use Case: Network Security Monitoring], [Data Source: Elastic Defend], [Data Source: PAN-OS] |
None |
7 |
|
This threshold rule monitors for the rapid execution of unix utilities that are capable of conducting network scans. Adversaries may leverage built-in tools such as ping, netcat or socat to execute ping sweeps across the network while attempting to evade detection or due to the lack of network mapping tools available on the compromised host. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
Adversaries may look for folders and drives shared on remote systems to identify sources of information to gather as a precursor for collection and identify potential systems of interest for Lateral Movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Rule Type: BBR], [Data Source: System] |
None |
6 |
|
This rule identifies a potential network sweep. A network sweep is a method used by attackers to scan a target network, identifying active hosts, open ports, and available services to gather information on vulnerabilities and weaknesses. This reconnaissance helps them plan subsequent attacks and exploit potential entry points for unauthorized access, data theft, or other malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination hosts on commonly used network services. |
[Domain: Network], [Tactic: Discovery], [Tactic: Reconnaissance], [Use Case: Network Security Monitoring], [Data Source: Elastic Defend], [Data Source: PAN-OS] |
None |
8 |
|
Identifies potentially malicious processes communicating via a port paring typically not associated with HTTP/HTTPS. For example, HTTP over port 8443 or port 440 as opposed to the traditional port 80 , 443. Adversaries may make changes to the standard port a protocol uses to bypass filtering or muddle analysis/parsing of network data. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Command and Control], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
5 |
|
Identifies potentially malicious processes communicating via a port paring typically not associated with SSH. For example, SSH over port 2200 or port 2222 as opposed to the traditional port 22. Adversaries may make changes to the standard port a protocol uses to bypass filtering or muddle analysis/parsing of network data. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [OS: macOS], [Data Source: Elastic Defend] |
None |
6 |
|
Detects when an attacker abuses the Multi-Factor authentication mechanism by repeatedly issuing login requests until the user eventually accepts the Okta push notification. An adversary may attempt to bypass the Okta MFA policies configured for an organization to obtain unauthorized access. |
[Use Case: Identity and Access Audit], [Tactic: Credential Access], [Data Source: Okta] |
None |
6 |
|
Identifies a Secure Shell (SSH) client or server process creating or writing to a known SSH backdoor log file. Adversaries may modify SSH related binaries for persistence or credential access via patching sensitive functions to enable unauthorized access or to log SSH credentials for exfiltration. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
110 |
|
Adversaries may attempt to connect to a remote system over Windows Remote Desktop Protocol (RDP) to achieve lateral movement. Adversaries may avoid using the Microsoft Terminal Services Client (mstsc.exe) binary to establish an RDP connection to evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
4 |
|
Adversaries may pass the hash using stolen password hashes to move laterally within an environment, bypassing normal system access controls. Pass the hash (PtH) is a method of authenticating as a user without having access to the user’s cleartext password. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: System] |
None |
6 |
|
Identifies modifications to the Atom desktop text editor Init File. Adversaries may add malicious JavaScript code to the init.coffee file that will be executed upon the Atom application opening. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
106 |
|
This rule leverages the File Integrity Monitoring (FIM) integration to detect file modifications of files that are commonly used for persistence on Linux systems. The rule detects modifications to files that are commonly used for cron jobs, systemd services, message-of-the-day (MOTD), SSH configurations, shell configurations, runtime control, init daemon, passwd/sudoers/shadow files, Systemd udevd, and XDG/KDE autostart entries. To leverage this rule, the paths specified in the query need to be added to the FIM policy in the Elastic Security app. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: File Integrity Monitoring] |
None |
4 |
|
Identifies the creation or modification of the login window property list (plist). Adversaries may modify plist files to run a program during system boot or user login for persistence. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
108 |
|
Identifies the creation or modification of the default configuration for periodic tasks. Adversaries may abuse periodic tasks to execute malicious code or maintain persistence. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies modification of the Time Provider. Adversaries may establish persistence by registering and enabling a malicious DLL as a time provider. Windows uses the time provider architecture to obtain accurate time stamps from other network devices or clients in the network. Time providers are implemented in the form of a DLL file which resides in the System32 folder. The service W32Time initiates during the startup of Windows and loads w32time.dll. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Potential Port Monitor or Print Processor Registration Abuse |
Identifies port monitor and print processor registry modifications. Adversaries may abuse port monitor and print processors to run malicious DLLs during system boot that will be executed as SYSTEM for privilege escalation and/or persistence, if permissions allow writing a fully-qualified pathname for that DLL. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint] |
None |
108 |
Detects known PowerShell offensive tooling author’s name in PowerShell scripts. Attackers commonly use out-of-the-box offensive tools without modifying the code, which may still contain the author artifacts. This rule identifies common author handles found in popular PowerShell scripts used for red team exercises. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: PowerShell Logs] |
None |
4 |
|
Detects known PowerShell offensive tooling functions names in PowerShell scripts. Attackers commonly use out-of-the-box offensive tools without modifying the code. This rule aim is to take advantage of that. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: PowerShell Logs] |
8.12.0 |
113 |
|
Identifies scripts that contain patterns and known methods that obfuscate PowerShell code. Attackers can use obfuscation techniques to bypass PowerShell security protections such as Antimalware Scan Interface (AMSI). |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs] |
None |
3 |
|
Detects PowerShell scripts that can execute pass-the-hash (PtH) attacks, intercept and relay NTLM challenges, and carry out other man-in-the-middle (MitM) attacks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
4 |
|
Identifies use of the Secure Copy Protocol (SCP) to copy files locally by abusing the auto addition of the Secure Shell Daemon (sshd) to the authorized application list for Full Disk Access. This may indicate attempts to bypass macOS privacy controls to access sensitive files. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies the use of sqlite3 to directly modify the Transparency, Consent, and Control (TCC) SQLite database. This may indicate an attempt to bypass macOS privacy controls, including access to sensitive resources like the system camera, microphone, address book, and calendar. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
107 |
|
Potential Privilege Escalation through Writable Docker Socket |
This rule monitors for the usage of Docker runtime sockets to escalate privileges on Linux systems. Docker sockets by default are only be writable by the root user and docker group. Attackers that have permissions to write to these sockets may be able to create and run a container that allows them to escalate privileges and gain further access onto the host file system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Domain: Container], [Data Source: Elastic Defend] |
None |
5 |
This rule detects potential privilege escalation attempts through Looney Tunables (CVE-2023-4911). Looney Tunables is a buffer overflow vulnerability in GNU C Library’s dynamic loader’s processing of the GLIBC_TUNABLES environment variable. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
4 |
|
Potential Privilege Escalation via Container Misconfiguration |
This rule monitors for the execution of processes that interact with Linux containers through an interactive shell without root permissions. Utilities such as runc and ctr are universal command-line utilities leveraged to interact with containers via root permissions. On systems where the access to these utilities are misconfigured, attackers might be able to create and run a container that mounts the root folder or spawn a privileged container vulnerable to a container escape attack, which might allow them to escalate privileges and gain further access onto the host file system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Domain: Container], [Data Source: Elastic Defend] |
None |
5 |
Identifies an attempt to exploit a local privilege escalation CVE-2022-37706 via a flaw in Linux window manager package Enlightenment. enlightenment_sys in Enlightenment before 0.25.4 allows local users to gain privileges because it is setuid root, and the system library function mishandles pathnames that begin with a /dev/.. substring. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies a potential exploitation of InstallerTakeOver (CVE-2021-41379) default PoC execution. Successful exploitation allows an unprivileged user to escalate privileges to SYSTEM. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
111 |
|
Identifies potential privilege escalation exploitation of DAC (Discretionary access control) file permissions. The rule identifies exploitation of DAC checks on sensitive file paths via suspicious processes whose capabilities include CAP_DAC_OVERRIDE (where a process can bypass all read write and execution checks) or CAP_DAC_READ_SEARCH (where a process can read any file or perform any executable permission on the directories). |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies an attempt to exploit a local privilege escalation (CVE-2023-2640 and CVE-2023-32629) via a flaw in Ubuntu’s modifications to OverlayFS. These flaws allow the creation of specialized executables, which, upon execution, grant the ability to escalate privileges to root on the affected machine. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
5 |
|
Identifies an attempt to exploit a local privilege escalation in polkit pkexec (CVE-2021-4034) via unsecure environment variable injection. Successful exploitation allows an unprivileged user to escalate to the root user. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
108 |
|
This detection rule monitors for the execution of a system command with setuid or setgid capabilities via Python, followed by a uid or gid change to the root user. This sequence of events may indicate successful privilege escalation. Setuid (Set User ID) and setgid (Set Group ID) are Unix-like OS features that enable processes to run with elevated privileges, based on the file owner or group. Threat actors can exploit these attributes to escalate privileges to the privileges that are set on the binary that is being executed. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
3 |
|
Potential Privilege Escalation via Recently Compiled Executable |
This rule monitors a sequence involving a program compilation event followed by its execution and a subsequent alteration of UID permissions to root privileges. This behavior can potentially indicate the execution of a kernel or software privilege escalation exploit. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
4 |
Potential Privilege Escalation via Service ImagePath Modification |
Identifies registry modifications to default services that could enable privilege escalation to SYSTEM. Attackers with privileges from groups like Server Operators may change the ImagePath of services to executables under their control or to execute commands. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
2 |
Potential Privilege Escalation via Sudoers File Modification |
A sudoers file specifies the commands users or groups can run and from which terminals. Adversaries can take advantage of these configurations to execute commands as other users or spawn processes with higher privileges. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
104 |
This rule monitors for the execution of the systemd-run command by a user with a UID that is larger than the maximum allowed UID size (INT_MAX). Some older Linux versions were affected by a bug which allows user accounts with a UID greater than INT_MAX to escalate privileges by spawning a shell through systemd-run. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
5 |
|
Identifies a suspicious computer account name rename event, which may indicate an attempt to exploit CVE-2021-42278 to elevate privileges from a standard domain user to a user with domain admin privileges. CVE-2021-42278 is a security vulnerability that allows potential attackers to impersonate a domain controller via samAccountName attribute spoofing. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Use Case: Vulnerability], [Data Source: System] |
None |
109 |
|
Identifies child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, Excel) with unusual process arguments and path. This behavior is often observed during exploitation of Office applications or from documents with malicious macros. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
2 |
|
Detects the use of Windows API functions that are commonly abused by malware and security tools to load malicious code or inject it into remote processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
113 |
|
This rule monitors for common command line flags leveraged by the Chisel client utility followed by a connection attempt. Chisel is a command-line utility used for creating and managing TCP and UDP tunnels, enabling port forwarding and secure communication between machines. Attackers can abuse the Chisel utility to establish covert communication channels, bypass network restrictions, and carry out malicious activities by creating tunnels that allow unauthorized access to internal systems. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
6 |
|
This rule monitors for common command line flags leveraged by the Chisel server utility followed by a received connection within a timespan of 1 minute. Chisel is a command-line utility used for creating and managing TCP and UDP tunnels, enabling port forwarding and secure communication between machines. Attackers can abuse the Chisel utility to establish covert communication channels, bypass network restrictions, and carry out malicious activities by creating tunnels that allow unauthorized access to internal systems. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
6 |
|
Identifies the execution of the EarthWorm tunneler. Adversaries may tunnel network communications to and from a victim system within a separate protocol to avoid detection and network filtering, or to enable access to otherwise unreachable systems. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
110 |
|
This rule leverages auditd to monitor for processes scanning different processes within the /proc directory using the openat syscall. This is a strong indication for the usage of the pspy utility. Attackers may leverage the pspy process monitoring utility to monitor system processes without requiring root permissions, in order to find potential privilege escalation vectors. |
[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery] |
None |
8 |
|
Potential Ransomware Behavior - High count of Readme files by System |
This rule identifies a high number (20) of file creation event by the System virtual process from the same host and with same file name containing keywords similar to ransomware note files and all within a short time period. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
107 |
Identifies an incoming SMB connection followed by the creation of a file with a name similar to ransomware note files. This may indicate a remote ransomware attack via the SMB protocol. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies potential relay attacks against a domain controller (DC) by identifying authentication events using the domain controller computer account coming from other hosts to the DC that owns the account. Attackers may relay the DC hash after capturing it using forced authentication. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Active Directory], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
2 |
|
Identifies suspicious commands executed via a web server, which may suggest a vulnerability and remote shell access. Attackers may exploit a vulnerability in a web application to execute commands via a web server, or place a backdoor file that can be abused to gain code execution as a mechanism for persistence. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
7 |
|
Identifies remote access to the registry to potentially dump credential data from the Security Account Manager (SAM) registry hive in preparation for credential access and privileges elevation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
111 |
|
Identifies the modification of the Remote Desktop Protocol (RDP) Shadow registry or the execution of processes indicative of an active RDP shadowing session. An adversary may abuse the RDP Shadowing feature to spy on or control other users active RDP sessions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Identifies potential use of an SSH utility to establish RDP over a reverse SSH Tunnel. This can be used by attackers to enable routing of network packets that would otherwise not reach their intended destination. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
8.13.0 |
315 |
|
Identifies the execution of the built-in Windows Installer, msiexec.exe, to install a remote package. Adversaries may abuse msiexec.exe to launch local or network accessible MSI files. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
3 |
|
This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a parent-child relationship where a network event is followed by the creation of a shell process. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
9 |
|
Identifies the execution of a shell process with suspicious arguments which may be indicative of reverse shell activity. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
109 |
|
Monitors for the execution of background processes with process arguments capable of opening a socket in the /dev/tcp channel. This may indicate the creation of a backdoor reverse connection, and should be investigated further. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
4 |
|
This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a network event that is followed by the creation of a shell process with suspicious command line arguments. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
3 |
|
This detection rule identifies the execution of a Linux shell process from a Java JAR application post an incoming network connection. This behavior may indicate reverse shell activity via a Java application. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
8 |
|
This detection rule detects the creation of a shell through a chain consisting of the execution of a suspicious binary (located in a commonly abused location or executed manually) followed by a network event and ending with a shell being spawned. Stageless reverse tcp shells display this behaviour. Attackers may spawn reverse shells to establish persistence onto a target system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
7 |
|
This detection rule detects the creation of a shell through a suspicious process chain. Any reverse shells spawned by the specified utilities that are initialized from a single process followed by a network connection attempt will be captured through this rule. Attackers may spawn reverse shells to establish persistence onto a target system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
9 |
|
This detection rule identifies suspicious network traffic patterns associated with UDP reverse shell activity. This activity consists of a sample of an execve, socket and connect syscall executed by the same process, where the auditd.data.a0-1 indicate a UDP connection, ending with an egress connection event. An attacker may establish a Linux UDP reverse shell to bypass traditional firewall restrictions and gain remote access to a target system covertly. |
[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |
None |
7 |
|
Identifies processes that are capable of downloading files with command line arguments containing URLs to SSH-IT’s autonomous SSH worm. This worm intercepts outgoing SSH connections every time a user uses ssh. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
This rule identifies a potential SYN-Based port scan. A SYN port scan is a technique employed by attackers to scan a target network for open ports by sending SYN packets to multiple ports and observing the response. Attackers use this method to identify potential entry points or services that may be vulnerable to exploitation, allowing them to launch targeted attacks or gain unauthorized access to the system or network, compromising its security and potentially leading to data breaches or further malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination ports using 2 or less packets per port. |
[Domain: Network], [Tactic: Discovery], [Tactic: Reconnaissance], [Use Case: Network Security Monitoring], [Data Source: Elastic Defend], [Data Source: PAN-OS] |
None |
7 |
|
Detects file name patterns generated by the use of Sysinternals SDelete utility to securely delete a file via multiple file overwrite and rename operations. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Impact], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Identify the modification of the msDS-KeyCredentialLink attribute in an Active Directory Computer or User Object. Attackers can abuse control over the object and create a key pair, append to raw public key in the attribute, and obtain persistent and stealthy access to the target user or computer object. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
112 |
|
Identifies access to the /etc/shadow file via the commandline using standard system utilities. After elevating privileges to root, threat actors may attempt to read or dump this file in order to gain valid credentials. They may utilize these to move laterally undetected and access additional resources. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
209 |
|
Identifies potential behavior of SharpRDP, which is a tool that can be used to perform authenticated command execution against a remote target via Remote Desktop Protocol (RDP) for the purposes of lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |
None |
108 |
|
This rule monitors for the execution of a set of linux binaries, that are potentially vulnerable to wildcard injection, with suspicious command line flags followed by a shell spawn event. Linux wildcard injection is a type of security vulnerability where attackers manipulate commands or input containing wildcards (e.g., *, ?, []) to execute unintended operations or access sensitive data by tricking the system into interpreting the wildcard characters in unexpected ways. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
6 |
|
An FTP (file transfer protocol) brute force attack is a method where an attacker systematically tries different combinations of usernames and passwords to gain unauthorized access to an FTP server, and if successful, the impact can include unauthorized data access, manipulation, or theft, compromising the security and integrity of the server and potentially exposing sensitive information. This rule identifies multiple consecutive authentication failures targeting a specific user account from the same source address and within a short time interval, followed by a successful authentication. |
[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |
None |
7 |
|
An RDP (Remote Desktop Protocol) brute force attack involves an attacker repeatedly attempting various username and password combinations to gain unauthorized access to a remote computer via RDP, and if successful, the potential impact can include unauthorized control over the compromised system, data theft, or the ability to launch further attacks within the network, jeopardizing the security and confidentiality of the targeted system and potentially compromising the entire network infrastructure. This rule identifies multiple consecutive authentication failures targeting a specific user account within a short time interval, followed by a successful authentication. |
[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |
None |
7 |
|
Identifies multiple SSH login failures followed by a successful one from the same source address. Adversaries can attempt to login into multiple users with a common or known password to gain access to accounts. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |
None |
11 |
|
Identifies the creation of a sudo binary located at /usr/bin/sudo. Attackers may hijack the default sudo binary and replace it with a custom binary or script that can read the user’s password in clear text to escalate privileges or enable persistence onto the system every time the sudo binary is executed. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
107 |
|
This rule monitors for the execution of a suspicious sudo command that is leveraged in CVE-2019-14287 to escalate privileges to root. Sudo does not verify the presence of the designated user ID and proceeds to execute using a user ID that can be chosen arbitrarily. By using the sudo privileges, the command "sudo -u#-1" translates to an ID of 0, representing the root user. This exploit may work for sudo versions prior to v1.28. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Use Case: Vulnerability], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
4 |
|
This rule detects potential sudo token manipulation attacks through process injection by monitoring the use of a debugger (gdb) process followed by a successful uid change event during the execution of the sudo process. A sudo token manipulation attack is performed by injecting into a process that has a valid sudo token, which can then be used by attackers to activate their own sudo token. This attack requires ptrace to be enabled in conjunction with the existence of a living process that has a valid sudo token with the same uid as the current user. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
5 |
|
This rule monitors for the usage of the built-in Linux DebugFS utility to access a disk device without root permissions. Linux users that are part of the "disk" group have sufficient privileges to access all data inside of the machine through DebugFS. Attackers may leverage DebugFS in conjunction with "disk" permissions to read sensitive files owned by root, such as the shadow file, root ssh private keys or other sensitive files that may allow them to further escalate privileges. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
6 |
|
This rule monitors for the potential edit of a suspicious file. In Linux, when editing a file through an editor, a temporary .swp file is created. By monitoring for the creation of this .swp file, we can detect potential file edits of suspicious files. The execution of this rule is not a clear sign of the file being edited, as just opening the file through an editor will trigger this event. Attackers may alter any of the files added in this rule to establish persistence, escalate privileges or perform reconnaisance on the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
5 |
|
Potential Unauthorized Access via Wildcard Injection Detected |
This rule monitors for the execution of the "chown" and "chmod" commands with command line flags that could indicate a wildcard injection attack. Linux wildcard injection is a type of security vulnerability where attackers manipulate commands or input containing wildcards (e.g., *, ?, []) to execute unintended operations or access sensitive data by tricking the system into interpreting the wildcard characters in unexpected ways. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
5 |
Identifies when a non-interactive terminal (tty) is being upgraded to a fully interactive shell. Attackers may upgrade a simple reverse shell to a fully interactive tty after obtaining initial access to a host, in order to obtain a more stable connection. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies commands that can access and decrypt Veeam credentials stored in MSSQL databases. Attackers can use Veeam Credentials to target backups as part of destructive operations such as Ransomware attacks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
102 |
|
Identifies the creation of a DNS record that is potentially meant to enable WPAD spoofing. Attackers can disable the Global Query Block List (GQBL) and create a "wpad" record to exploit hosts running WPAD with default settings for privilege escalation and lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
3 |
|
Identifies a potential Windows Server Update Services (WSUS) abuse to execute psexec to enable for lateral movement. WSUS is limited to executing Microsoft signed binaries, which limits the executables that can be used to tools published by Microsoft. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
8.13.0 |
104 |
|
Potential Widespread Malware Infection Across Multiple Hosts |
This rule uses alert data to determine when a malware signature is triggered in multiple hosts. Analysts can use this to prioritize triage and response, as this can potentially indicate a widespread malware infection. |
[Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Threat Detection], [Tactic: Execution], [Rule Type: Higher-Order Rule] |
8.13.0 |
2 |
Identifies suspicious instances of the Windows Error Reporting process (WerFault.exe or Wermgr.exe) with matching command-line and process executable values performing outgoing network connections. This may be indicative of a masquerading attempt to evade suspicious child process behavior detections. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
109 |
|
This detection rule identifies when SCNotification.exe loads an untrusted DLL, which is a potential indicator of an attacker attempt to hijack/impersonate a Windows user session. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
1 |
|
Detects potential exploitation of curl CVE-2023-38545 by monitoring for vulnerable command line arguments in conjunction with an unusual command line length. A flaw in curl version ⇐ 8.3 makes curl vulnerable to a heap based buffer overflow during the SOCKS5 proxy handshake. Upgrade to curl version >= 8.4 to patch this vulnerability. This exploit can be executed with and without the use of environment variables. For increased visibility, enable the collection of http_proxy, HTTPS_PROXY and ALL_PROXY environment variables based on the instructions provided in the setup guide of this rule. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Use Case: Vulnerability], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
6 |
|
Identifies a high number (20) of macOS SSH KeyGen process executions from the same host. An adversary may attempt a brute force attack to obtain unauthorized access to user accounts. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
108 |
|
Identifies a privilege escalation attempt via exploiting CVE-2022-38028 to hijack the print spooler service execution. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
103 |
|
Detects when an attacker abuses the Multi-Factor authentication mechanism by repeatedly issuing login requests until the user eventually accepts the Okta push notification. An adversary may attempt to bypass the Okta MFA policies configured for an organization to obtain unauthorized access. |
[Use Case: Identity and Access Audit], [Tactic: Credential Access], [Data Source: Okta] |
None |
212 |
|
This rule monitors for the execution of suspicious commands via screen and tmux. When launching a command and detaching directly, the commands will be executed in the background via its parent process. Attackers may leverage screen or tmux to execute commands while attempting to evade detection. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
5 |
|
Detects PowerShell scripts that contain the default exported functions used on Invoke-NinjaCopy. Attackers can use Invoke-NinjaCopy to read SYSTEM files that are normally locked, such as the NTDS.dit file or registry hives. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |
None |
8 |
|
Detects PowerShell scripts that have the capability of dumping Kerberos tickets from LSA, which potentially indicates an attacker’s attempt to acquire credentials for lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: PowerShell Logs] |
None |
7 |
|
Detects PowerShell scripts that have the capability of requesting kerberos tickets, which is a common step in Kerberoasting toolkits to crack service accounts. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
113 |
|
Detects the use of Win32 API Functions that can be used to capture user keystrokes in PowerShell scripts. Attackers use this technique to capture user input, looking for credentials and/or other valuable data. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
115 |
|
Detects PowerShell scripts that can be used to collect data from mailboxes. Adversaries may target user email to collect sensitive information. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |
None |
9 |
|
This rule detects PowerShell scripts capable of dumping process memory using WindowsErrorReporting or Dbghelp.dll MiniDumpWriteDump. Attackers can use this tooling to dump LSASS and get access to credentials. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
110 |
|
Detects the use of PSReflect in PowerShell scripts. Attackers leverage PSReflect as a library that enables PowerShell to access win32 API functions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
8.12.0 |
213 |
|
Identifies attempts to disable PowerShell Script Block Logging via registry modification. Attackers may disable this logging to conceal their activities in the host and evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies the use of Cmdlets and methods related to archive compression activities. Adversaries will often compress and encrypt data in preparation for exfiltration. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs], [Rule Type: BBR] |
8.12.0 |
108 |
|
Identifies the use of Cmdlets and methods related to discovery activities. Attackers can use these to perform various situational awareness related activities, like enumerating users, shares, sessions, domain trusts, groups, etc. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Discovery], [Data Source: PowerShell Logs], [Rule Type: BBR] |
8.12.0 |
109 |
|
Identifies the use of Cmdlets and methods related to encryption/decryption of files in PowerShell scripts, which malware and offensive security tools can abuse to encrypt data or decrypt payloads to bypass security solutions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |
None |
9 |
|
Identifies the use of Cmdlets and methods related to Windows event log deletion activities. This is often done by attackers in an attempt to evade detection or destroy forensic evidence on a system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs], [Rule Type: BBR] |
8.12.0 |
108 |
|
PowerShell Script with Password Policy Discovery Capabilities |
Identifies the use of Cmdlets and methods related to remote execution activities using WinRM. Attackers can abuse WinRM to perform lateral movement using built-in tools. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Execution], [Data Source: PowerShell Logs], [Rule Type: BBR] |
None |
7 |
PowerShell Script with Remote Execution Capabilities via WinRM |
Identifies the use of Cmdlets and methods related to remote execution activities using WinRM. Attackers can abuse WinRM to perform lateral movement using built-in tools. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Execution], [Data Source: PowerShell Logs], [Rule Type: BBR] |
8.12.0 |
108 |
Detects scripts that contain PowerShell functions, structures, or Windows API functions related to token impersonation/theft. Attackers may duplicate then impersonate another user’s token to escalate privileges and bypass access controls. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: PowerShell Logs] |
None |
14 |
|
Identifies PowerShell scripts that can access and decrypt Veeam credentials stored in MSSQL databases. Attackers can use Veeam Credentials to target backups as part of destructive operations such as Ransomware attacks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: PowerShell Logs] |
None |
3 |
|
Detects PowerShell scripts that can be used to record webcam video. Attackers can capture this information to extort or spy on victims. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs] |
None |
6 |
|
PowerShell Script with Windows Defender Tampering Capabilities |
Identifies PowerShell scripts containing cmdlets and parameters that attackers can abuse to disable Windows Defender features. Attackers can tamper with antivirus to reduce the risk of detection when executing their payloads. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs], [Rule Type: BBR] |
None |
3 |
Detects scripts that contain PowerShell functions, structures, or Windows API functions related to windows share enumeration activities. Attackers, mainly ransomware groups, commonly identify and inspect network shares, looking for critical information for encryption and/or exfiltration. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
11 |
|
PowerShell Suspicious Discovery Related Windows API Functions |
This rule detects the use of discovery-related Windows API functions in PowerShell Scripts. Attackers can use these functions to perform various situational awareness related activities, like enumerating users, shares, sessions, domain trusts, groups, etc. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
8.12.0 |
216 |
Identifies the use of .NET functionality for decompression and base64 decoding combined in PowerShell scripts, which malware and security tools heavily use to deobfuscate payloads and load them directly in memory to bypass defenses. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
8.12.0 |
214 |
|
PowerShell Suspicious Script with Audio Capture Capabilities |
Detects PowerShell scripts that can record audio, a common feature in popular post-exploitation tooling. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
112 |
PowerShell Suspicious Script with Clipboard Retrieval Capabilities |
Detects PowerShell scripts that can get the contents of the clipboard, which attackers can abuse to retrieve sensitive information like credentials, messages, etc. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |
8.12.0 |
110 |
Detects PowerShell scripts that can take screenshots, which is a common feature in post-exploitation kits and remote access tools (RATs). |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
110 |
|
This detection rule addresses multiple vulnerabilities in the CUPS printing system, including CVE-2024-47176, CVE-2024-47076, CVE-2024-47175, and CVE-2024-47177. Specifically, this rule detects shell executions from the foomatic-rip parent process through the default printer user (lp). These flaws impact components like cups-browsed, libcupsfilters, libppd, and foomatic-rip, allowing remote unauthenticated attackers to manipulate IPP URLs or inject malicious data through crafted UDP packets or network spoofing. This can result in arbitrary command execution when a print job is initiated. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Use Case: Vulnerability], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
2 |
|
This rule detects private key searching activity on Linux systems. Searching for private keys can be an indication of an attacker attempting to escalate privileges or exfiltrate sensitive information. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies instances where a processes (granted CAP_CHOWN and/or CAP_FOWNER capabilities) is executed, after which the ownership of a suspicious file or binary is changed. In Linux, the CAP_CHOWN capability allows a process to change the owner of a file, while CAP_FOWNER permits it to bypass permission checks on operations that require file ownership (like reading, writing, and executing). Attackers may abuse these capabilities to obtain unauthorized access to files. |
[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies instances where a process (granted CAP_SETUID and/or CAP_SETGID capabilities) is executed, after which the user’s access is elevated to UID/GID 0 (root). In Linux, the CAP_SETUID and CAP_SETGID capabilities allow a process to change its UID and GID, respectively, providing control over user and group identity management. Attackers may leverage a misconfiguration for exploitation in order to escalate their privileges to root. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
4 |
|
Identifies instances where GDB (granted the CAP_SYS_PTRACE capability) is executed, after which the user’s access is elevated to UID/GID 0 (root). In Linux, the CAP_SYS_PTRACE capability grants a process the ability to use the ptrace system call, which is typically used for debugging and allows the process to trace and control other processes. Attackers may leverage this capability to hook and inject into a process that is running with root permissions in order to escalate their privileges to root. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies a privilege escalation attempt via named pipe impersonation. An adversary may abuse this technique by utilizing a framework such Metasploit’s meterpreter getsystem command. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies a privilege escalation attempt via rogue named pipe impersonation. An adversary may abuse this technique by masquerading as a known named pipe and manipulating a privileged process to connect to it. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Sysmon] |
None |
106 |
|
Identifies modifications to the root crontab file. Adversaries may overwrite this file to gain code execution with root privileges by exploiting privileged file write or move related vulnerabilities. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies instances where a process is executed with user/group ID 0 (root), and a real user/group ID that is not 0. This is indicative of a process that has been granted SUID/SGID permissions, allowing it to run with elevated privileges. Attackers may leverage a misconfiguration for exploitation in order to escalate their privileges to root, or establish a backdoor for persistence. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies a privilege escalation attempt via a rogue Windows directory (Windir) environment variable. This is a known primitive that is often combined with other vulnerabilities to elevate privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
208 |
|
Identifies multiple consecutive logon failures targeting an Admin account from the same source address and within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: System] |
None |
10 |
|
This rule leverages the new_terms rule type to identify the creation of a potentially unsafe docker container from an unusual parent process. Attackers can use the |
[Domain: Endpoint], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies parent process spoofing used to create an elevated child process. Adversaries may spoof the parent process identifier (PPID) of a new process to evade process-monitoring defenses or to elevate privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
7 |
|
Compiled HTML files (.chm) are commonly distributed as part of the Microsoft HTML Help system. Adversaries may conceal malicious code in a CHM file and deliver it to a victim for execution. CHM content is loaded by the HTML Help executable program (hh.exe). |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies recursive process capability enumeration of the entire filesystem through the getcap command. Malicious users may manipulate identified capabilities to gain root privileges. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
2 |
|
This rule detects the use of the setcap utility to set capabilities on a process. The setcap utility is used to set the capabilities of a binary to allow it to perform privileged operations without needing to run as root. This can be used by attackers to establish persistence by creating a backdoor, or escalate privileges by abusing a misconfiguration on a system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies the creation of a process impersonating the token of another user logon session. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies the creation of a process running as SYSTEM and impersonating a Windows core binary privileges. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
6 |
|
Identifies process creation with alternate credentials. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: System] |
None |
10 |
|
This rule identifies the execution of commands that can be used to enumerate running processes. Adversaries may enumerate processes to identify installed applications and security solutions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: System] |
None |
6 |
|
Identifies the use of built-in tools attackers can use to discover running processes on an endpoint. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
3 |
|
Identifies process execution from suspicious default Windows directories. This is sometimes done by adversaries to hide malware in trusted paths. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Elastic Endgame detected Process Injection. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
103 |
|
Elastic Endgame prevented Process Injection. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |
None |
103 |
|
An instance of MSBuild, the Microsoft Build Engine, created a thread in another process. This technique is sometimes used to evade detection or elevate privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Data Source: Sysmon] |
None |
107 |
|
Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" directory. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. This rule detects the execution of potentially malicious processes through the MOTD utility. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
10 |
|
Identifies a new process starting from a process ID (PID), lock or reboot file within the temporary file storage paradigm (tmpfs) directory /var/run directory. On Linux, the PID files typically hold the process ID to track previous copies running and manage other tasks. Certain Linux malware use the /var/run directory for holding data, executables and other tasks, disguising itself or these files as legitimate PID files. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: BPFDoor], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |
None |
109 |
|
Identifies a process termination event quickly followed by the deletion of its executable file. Malware tools and other non-native files dropped or created on a system by an adversary may leave traces to indicate to what occurred. Removal of these files can occur during an intrusion, or as part of a post-intrusion process to minimize the adversary’s footprint. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
110 |
|
Identify instances where adversaries include trailing space characters to mimic regular files, disguising their activity to evade default file handling mechanisms. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
2 |
|
Identifies execution from a directory masquerading as the Windows Program Files directories. These paths are trusted and usually host trusted third party programs. An adversary may leverage masquerading, along with low privileges to bypass detections allowlisting those folders. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies the use of osascript to execute scripts via standard input that may prompt a user with a rogue dialog for credentials. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
208 |
|
This rule monitors for the execution of the ProxyChains utility. ProxyChains is a command-line tool that enables the routing of network connections through intermediary proxies, enhancing anonymity and enabling access to restricted resources. Attackers can exploit the ProxyChains utility to hide their true source IP address, evade detection, and perform malicious activities through a chain of proxy servers, potentially masking their identity and intentions. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
4 |
|
Identifies use of the SysInternals tool PsExec.exe making a network connection. This could be an indication of lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
109 |
|
Detects deletion of the quarantine attribute by an unusual process (xattr). In macOS, when applications or programs are downloaded from the internet, there is a quarantine flag set on the file. This attribute is read by Apple’s Gatekeeper defense program at execution time. An adversary may disable this attribute to evade defenses. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
109 |
|
This rule identifies the execution of commands that can be used to query the Windows Registry. Adversaries may query the registry to gain situational awareness about the host, like installed security software, programs and settings. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
105 |
|
This rule detects network events that may indicate the use of RDP traffic from the Internet. RDP is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |
[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection], [Data Source: PAN-OS] |
None |
104 |
|
Identifies registry write modifications to enable Remote Desktop Protocol (RDP) access. This could be indicative of adversary lateral movement preparation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies the execution of a Python script that uses the ROT cipher for letters substitution. Adversaries may use this method to encode and obfuscate part of their malicious code in legit python packages. |
[Domain: Endpoint], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
1 |
|
This rule detects network events that may indicate the use of RPC traffic from the Internet. RPC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |
[Tactic: Initial Access], [Domain: Endpoint], [Use Case: Threat Detection], [Data Source: PAN-OS] |
None |
104 |
|
This rule detects network events that may indicate the use of RPC traffic to the Internet. RPC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |
[Tactic: Initial Access], [Domain: Endpoint], [Use Case: Threat Detection], [Data Source: PAN-OS] |
None |
104 |
|
This rule leverages the new_terms rule type to identify the installation of RPM packages by an unusual parent process. RPM is a package management system used in Linux systems such as Red Hat, CentOS and Fedora. Attacks may backdoor RPM packages to gain initial access or install malicious RPM packages to maintain persistence. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
2 |
|
Elastic Endgame detected ransomware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame] |
None |
103 |
|
Elastic Endgame prevented ransomware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |
[Data Source: Elastic Endgame] |
None |
103 |
|
This rule attempts to identify rapid secret retrieval attempts from AWS SecretsManager. Adversaries may attempt to retrieve secrets from the Secrets Manager programmatically using the |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Secrets Manager], [Tactic: Credential Access], [Resources: Investigation Guide] |
None |
1 |
|
This rule is triggered when CVEs collected from the Rapid7 Threat Command Integration have a match against vulnerabilities that were found in the customer environment. |
[OS: Windows], [Data Source: Elastic Endgame], [Data Source: Windows], [Data Source: Network], [Data Source: Rapid7 Threat Command], [Rule Type: Threat Match], [Resources: Investigation Guide], [Use Case: Vulnerability], [Use Case: Asset Visibility], [Use Case: Continuous Monitoring] |
8.13.0 |
103 |
|
A machine learning job detected an unusual error in a CloudTrail message. These can be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |
None |
209 |
|
This rule detects rare internet network connections via the SMB protocol. SMB is commonly used to leak NTLM credentials via rogue UNC path injection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Exfiltration], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
108 |
|
A machine learning job found an unusual user name in the authentication logs. An unusual user name is one way of detecting credentialed access by means of a new or dormant user account. An inactive user account (because the user has left the organization) that becomes active may be due to credentialed access using a compromised account password. Threat actors will sometimes also create new users as a means of persisting in a compromised web application. |
[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access], [Resources: Investigation Guide] |
None |
105 |
|
Detects attempts to maintain persistence by creating registry keys using AppCert DLLs. AppCert DLLs are loaded by every process using the common API functions to create processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
312 |
|
AppInit DLLs are dynamic-link libraries (DLLs) that are loaded into every process that creates a user interface (loads user32.dll) on Microsoft Windows operating systems. The AppInit DLL mechanism is used to load custom code into user-mode processes, allowing for the customization of the user interface and the behavior of Windows-based applications. Attackers who add those DLLs to the registry locations can execute code with elevated privileges, similar to process injection, and provide a solid and constant persistence on the machine. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies the remote update to a computer account’s DnsHostName attribute. If the new value set is a valid domain controller DNS hostname and the subject computer name is not a domain controller, then it’s highly likely a preparation step to exploit CVE-2022-26923 in an attempt to elevate privileges from a standard domain user to domain admin privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Use Case: Vulnerability], [Data Source: System] |
None |
108 |
|
Identifies use of the network shell utility (netsh.exe) to enable inbound Remote Desktop Protocol (RDP) connections in the Windows Firewall. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies the execution of a file that was created by the virtual system process. This may indicate lateral movement via network file shares. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
114 |
|
Identifies a remote file copy attempt to a hidden network share. This may indicate lateral movement or data staging activity. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies an executable or script file remotely downloaded via a TeamViewer transfer session. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies the desktopimgdownldr utility being used to download a remote file. An adversary may use desktopimgdownldr to download arbitrary files as an alternative to certutil. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Sysmon] |
8.13.0 |
213 |
|
Identifies the Windows Defender configuration utility (MpCmdRun.exe) being used to download a remote file. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Identifies powershell.exe being used to download an executable file from an untrusted remote destination. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
110 |
|
Identifies built-in Windows script interpreters (cscript.exe or wscript.exe) being used to download an executable file from a remote destination. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
110 |
|
Detects use of the systemsetup command to enable remote SSH Login. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies remote scheduled task creations on a target host. This could be indicative of adversary lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
110 |
|
Identifies scheduled task creation from a remote source. This could be indicative of adversary lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: System] |
None |
9 |
|
Discovery of remote system information using built-in commands, which may be used to move laterally. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR] |
None |
114 |
|
Identifies a network logon followed by Windows service creation with same LogonId. This could be indicative of lateral movement, but will be noisy if commonly done by administrators." |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence], [Data Source: System] |
None |
7 |
|
Identifies the execution of a hosted XSL script using the Microsoft.XMLDOM COM interface via Microsoft Office processes. This behavior may indicate adversarial activity to execute malicious JScript or VBScript on the system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies remote execution of Windows services over remote procedure call (RPC). This could be indicative of lateral movement, but will be noisy if commonly done by administrators. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
113 |
|
Identifies a suspicious AutoIt process execution. Malware written as an AutoIt script tends to rename the AutoIt executable to avoid detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
111 |
|
Identifies the execution of a process with a single character process name, differing from the original file name. This is often done by adversaries while staging, executing temporary utilities, or trying to bypass security detections based on the process name. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
110 |
|
This rule detects the installation of root certificates on a Linux system. Adversaries may install a root certificate on a compromised system to avoid warnings when connecting to their command and control servers. Root certificates are used in public key cryptography to identify a root certificate authority (CA). When a root certificate is installed, the system or application will trust certificates in the root’s chain of trust that have been signed by the root certificate. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies instances where GDB (granted the CAP_SYS_PTRACE capability) is executed, after which an outbound network connection is initiated by UID/GID 0 (root). In Linux, the CAP_SYS_PTRACE capability grants a process the ability to use the ptrace system call, which is typically used for debugging and allows the process to trace and control other processes. Attackers may leverage this capability to hook and inject into a process that is running with root permissions in order to execute shell code and gain a reverse shell with root privileges. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Execution], [Tactic: Command and Control], [Data Source: Elastic Defend] |
None |
2 |
|
Roshal Archive (RAR) or PowerShell File Downloaded from the Internet |
Detects a Roshal Archive (RAR) file or PowerShell script downloaded from the internet by an internal host. Gaining initial access to a system and then downloading encoded or encrypted tools to move laterally is a common practice for adversaries as a way to protect their more valuable tools and tactics, techniques, and procedures (TTPs). This may be atypical behavior for a managed network and can be indicative of malware, exfiltration, or command and control. |
[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint], [Data Source: PAN-OS] |
None |
104 |
Identifies when a Route53 Resolver Query Log Configuration is deleted. When a Route53 Resolver query log configuration is deleted, Resolver stops logging DNS queries and responses for the specified configuration. Adversaries may delete query log configurations to evade detection or cover their tracks. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon Route53], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |
None |
2 |
|
This rule detects the creation or renaming of the SELinux configuration file. SELinux is a security module that provides access control security policies. Modifications to the SELinux configuration file may indicate an attempt to impair defenses by disabling or modifying security tools. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies modifications to the registered Subject Interface Package (SIP) providers. SIP providers are used by the Windows cryptographic system to validate file signatures on the system. This may be an attempt to bypass signature validation checks or inject code into critical processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
This rule detects network events that may indicate the use of Windows file sharing (also called SMB or CIFS) traffic to the Internet. SMB is commonly used within networks to share files, printers, and other system resources amongst trusted systems. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector or for data exfiltration. |
[Tactic: Initial Access], [Domain: Endpoint], [Use Case: Threat Detection], [Data Source: PAN-OS] |
None |
104 |
|
Identifies potentially suspicious processes that are not trusted or living-off-the-land binaries (LOLBin) making Server Message Block (SMB) network connections over port 445. Windows File Sharing is typically implemented over SMB, which communicates between hosts using port 445. Legitimate connections are generally established by the kernel (PID 4). This rule helps to detect processes that might be port scanners, exploits, or user-level processes attempting lateral movement within the network by leveraging SMB connections. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
112 |
|
This rule detects events that may indicate use of SMTP on TCP port 26. This port is commonly used by several popular mail transfer agents to deconflict with the default SMTP port 25. This port has also been used by a malware family called BadPatch for command and control of Windows systems. |
[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection], [Data Source: PAN-OS] |
None |
105 |
|
The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s). |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
206 |
|
This rule detects the creation or modification of an authorized_keys or sshd_config file inside a container. The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s). Unexpected and unauthorized SSH usage inside a container can be an indicator of compromise and should be investigated. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Lateral Movement] |
None |
3 |
|
This rule detects an incoming SSH connection established inside a running container. Running an ssh daemon inside a container should be avoided and monitored closely if necessary. If an attacker gains valid credentials they can use it to gain initial access or establish persistence within a compromised environment. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement] |
None |
2 |
|
This rule identifies the creation of SSH keys using the ssh-keygen tool, which is the standard utility for generating SSH keys. Users often create SSH keys for authentication with remote services. However, threat actors can exploit this tool to move laterally across a network or maintain persistence by generating unauthorized SSH keys, granting them SSH access to systems. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
3 |
|
This rule detects an SSH or SSHD process executed from inside a container. This includes both the client ssh binary and server ssh daemon process. SSH usage inside a container should be avoided and monitored closely when necessary. With valid credentials an attacker may move laterally to other containers or to the underlying host through container breakout. They may also use valid SSH credentials as a persistence mechanism. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence] |
None |
2 |
|
This rule detects the deletion of SSL certificates on a Linux system. Adversaries may delete SSL certificates to subvert trust controls and negatively impact the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Impact], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies the first occurrence of an AWS resource establishing a session via SSM to an EC2 instance. Adversaries may use AWS Systems Manager to establish a session to an EC2 instance to execute commands on the instance. This can be used to gain access to the instance and perform actions such as privilege escalation. This rule helps detect the first occurrence of this activity for a given AWS resource. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS SSM], [Use Case: Threat Detection], [Tactic: Lateral Movement] |
None |
1 |
|
An adversary may add the setuid or setgid bit to a file or directory in order to run a file with the privileges of the owning user or group. An adversary can take advantage of this to either do a shell escape or exploit a vulnerability in an application with the setuid or setgid bit to get code running in a different user’s context. Additionally, adversaries can use this mechanism on their own malware to make sure they’re able to execute in elevated contexts in the future. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
105 |
|
This rule monitors for the usage of the "find" command in conjunction with SUID and SGUID permission arguments. SUID (Set User ID) and SGID (Set Group ID) are special permissions in Linux that allow a program to execute with the privileges of the file owner or group, respectively, rather than the privileges of the user running the program. In case an attacker is able to enumerate and find a binary that is misconfigured, they might be able to leverage this misconfiguration to escalate privileges by exploiting vulnerabilities or built-in features in the privileged program. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
6 |
|
The malware known as SUNBURST targets the SolarWind’s Orion business software for command and control. This rule detects post-exploitation command and control activity of the SUNBURST backdoor. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
108 |
|
A scheduled task was created by a Windows script via cscript.exe, wscript.exe or powershell.exe. This can be abused by an adversary to establish persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Detects the modification of Group Policy Object attributes to execute a scheduled task in the objects controlled by the GPO. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Lateral Movement], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
112 |
|
Identifies attempts to enable the Windows scheduled tasks AT command via the registry. Attackers may use this method to move laterally or persist locally. The AT command has been deprecated since Windows 8 and Windows Server 2012, but still exists for backwards compatibility. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies suspicious processes being spawned by the ScreenConnect server process (ScreenConnect.Service.exe). This activity may indicate exploitation activity or access to an existing web shell backdoor. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
102 |
|
Identifies when a screensaver plist file is modified by an unexpected process. An adversary can maintain persistence on a macOS endpoint by creating a malicious screensaver (.saver) file and configuring the screensaver plist file to execute code each time the screensaver is activated. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies the execution of scripts via HTML applications using Windows utilities rundll32.exe or mshta.exe. Adversaries may bypass process and/or signature-based defenses by proxying execution of malicious content with signed binaries. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: System], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
101 |
|
Identifies the creation of a process running as SYSTEM and impersonating a Windows core binary privileges. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: System] |
None |
8 |
|
Windows Credential Manager allows you to create, view, or delete saved credentials for signing into websites, connected applications, and networks. An adversary may abuse this to list or dump credentials stored in the Credential Manager for saved usernames and passwords. This may also be performed in preparation of lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
This rule detects sensitive security file access via common utilities on Linux systems. Adversaries may attempt to read from sensitive files using common utilities to gather information about the system and its security configuration. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies the use of Windows Management Instrumentation Command (WMIC) to discover certain System Security Settings such as AntiVirus or Host Firewall details. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: System] |
None |
114 |
|
Identifies the use of the grep command to discover known third-party macOS and Linux security tools, such as Antivirus or Host Firewall details. |
[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
110 |
|
Monitors kernel logs for segfault messages. A segfault, or segmentation fault, is an error that occurs when a program tries to access a memory location that it’s not allowed to access, typically leading to program termination. A segfault can be an indication of malicious behavior if it results from attempts to exploit buffer overflows or other vulnerabilities in software to execute arbitrary code or disrupt its normal operation. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Rule Type: BBR] |
None |
1 |
|
Identifies the use of a compression utility to collect known files containing sensitive information, such as credentials and system configurations. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
208 |
|
Identifies the use of a compression utility to collect known files containing sensitive information, such as credentials and system configurations inside a container. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Credential Access] |
None |
2 |
|
This rule detects the use of system search utilities like grep and find to search for private SSH keys or passwords inside a container. Unauthorized access to these sensitive files could lead to further compromise of the container environment or facilitate a container breakout to the underlying host machine. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |
None |
2 |
|
Sensitive Privilege SeEnableDelegationPrivilege assigned to a User |
Identifies the assignment of the SeEnableDelegationPrivilege sensitive "user right" to a user. The SeEnableDelegationPrivilege "user right" enables computer and user accounts to be trusted for delegation. Attackers can abuse this right to compromise Active Directory accounts and elevate their privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
113 |
Identifies attempts to access sensitive registry hives which contain credentials from the registry backup folder. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies use of sc.exe to create, modify, or start services on remote hosts. This could be indicative of adversary lateral movement but will be noisy if commonly done by admins. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
107 |
|
Identifies Service Control (sc.exe) spawning from script interpreter processes to create, modify, or start services. This can potentially indicate an attempt to elevate privileges or maintain persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint] |
None |
112 |
|
Identifies a suspicious local successful logon event where the Logon Package is Kerberos, the remote address is set to localhost, followed by a sevice creation from the same LogonId. This may indicate an attempt to leverage a Kerberos relay attack variant that can be used to elevate privilege locally from a domain joined user to local System privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Data Source: System] |
None |
106 |
|
Identifies DACL modifications to deny access to a service, making it unstoppable, or hide it from system and users. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
103 |
|
Identifies attempts to modify services start settings using processes other than services.exe. Attackers may attempt to modify security and monitoring services to avoid detection or delay response. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
3 |
|
Identifies attempts to modify a service path by an unusual process. Attackers may attempt to modify existing services for persistence or privilege escalation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Sysmon] |
None |
5 |
|
Identifies attempts to modify a service path setting using sc.exe. Attackers may attempt to modify existing services for persistence or privilege escalation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Sysmon], [Data Source: System] |
None |
6 |
|
This rule monitors for the addition of the cap_setuid+ep or cap_setgid+ep capabilities via setcap. Setuid (Set User ID) and setgid (Set Group ID) are Unix-like OS features that enable processes to run with elevated privileges, based on the file owner or group. Threat actors can exploit these attributes to achieve persistence by creating malicious binaries, allowing them to maintain control over a compromised system with elevated permissions. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
6 |
|
This rule monitors for Linux Shadow file modifications. These modifications are indicative of a potential password change or user addition event. Threat actors may attempt to create new users or change the password of a user account to maintain access to a system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies the occurence of files uploaded to SharePoint being detected as Malware by the file scanning engine. Attackers can use File Sharing and Organization Repositories to spread laterally within the company and amplify their access. Users can inadvertently share these files without knowing their maliciousness, giving adversaries opportunities to gain initial access to other endpoints in the environment. |
[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Lateral Movement] |
None |
206 |
|
Shared Object Created or Changed by Previously Unknown Process |
This rule monitors the creation of shared object files by previously unknown processes. The creation of a shared object file involves compiling code into a dynamically linked library that can be loaded by other programs at runtime. While this process is typically used for legitimate purposes, malicious actors can leverage shared object files to execute unauthorized code, inject malicious functionality into legitimate processes, or bypass security controls. This allows malware to persist on the system, evade detection, and potentially compromise the integrity and confidentiality of the affected system and its data. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
9 |
This rule monitors the creation/alteration of a shell configuration file. Unix systems use shell configuration files to set environment variables, create aliases, and customize the user’s environment. Adversaries may modify or add a shell configuration file to execute malicious code and gain persistence in the system. This behavior is consistent with the Kaiji malware family. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
5 |
|
Identifies the execution of the shell process (sh) via scripting (JXA or AppleScript). Adversaries may use the doShellScript functionality in JXA or do shell script in AppleScript to execute system commands. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies shortcut files written to or modified in the startup folder. Adversaries may use this technique to maintain persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
2 |
|
Identifies the use of Windows Work Folders to execute a potentially masqueraded control.exe file in the current working directory. Misuse of Windows Work Folders could indicate malicious activity. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Identifies changes to the SoftwareUpdate preferences using the built-in defaults command. Adversaries may abuse this in an attempt to disable security updates. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies a SolarWinds binary modifying the start type of a service to be disabled. An adversary may abuse this technique to manipulate relevant security services. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
A machine learning job detected a significant spike in the rate of a particular error in the CloudTrail messages. Spikes in error messages may accompany attempts at privilege escalation, lateral movement, or discovery. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |
None |
209 |
|
A machine learning job has detected high bytes of data written to an external device. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities. |
[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |
None |
4 |
|
A machine learning job has detected high bytes of data written to an external device via Airdrop. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities. |
[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |
None |
4 |
|
A machine learning job found an unusually large spike in authentication failure events. This can be due to password spraying, user enumeration or brute force activity and may be a precursor to account takeover or credentialed access. |
[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access], [Resources: Investigation Guide] |
None |
105 |
|
A machine learning job detected an unusually large spike in network traffic that was denied by network access control lists (ACLs) or firewall rules. Such a burst of denied traffic is usually caused by either 1) a mis-configured application or firewall or 2) suspicious or malicious activity. Unsuccessful attempts at network transit, in order to connect to command-and-control (C2), or engage in data exfiltration, may produce a burst of failed connections. This could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic. |
[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |
None |
104 |
|
A machine learning job found an unusually large spike in successful authentication events. This can be due to password spraying, user enumeration or brute force activity. |
[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |
None |
104 |
|
A machine learning job detected an unusually large spike in network traffic. Such a burst of traffic, if not caused by a surge in business activity, can be due to suspicious or malicious activity. Large-scale data exfiltration may produce a burst of network traffic; this could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic. |
[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |
None |
104 |
|
A machine learning job detected an unusually large spike in network activity to one destination country in the network logs. This could be due to unusually large amounts of reconnaissance or enumeration traffic. Data exfiltration activity may also produce such a surge in traffic to a destination country that does not normally appear in network traffic or business workflows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network. |
[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |
None |
105 |
|
A machine learning job has detected a high count of destination IPs establishing an RDP connection with a single source IP. Once an attacker has gained access to one system, they might attempt to access more in the network in search of valuable assets, data, or further access points. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
A machine learning job has detected a high count of source IPs establishing an RDP connection with a single destination IP. Attackers might use multiple compromised systems to attack a target to ensure redundancy in case a source IP gets detected and blocked. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
A machine learning job has detected unusually high number of processes started in a single RDP session. Executing a large number of processes remotely on other machines can be an indicator of lateral movement activity. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
A machine learning job has detected an abnormal volume of remote files shared on the host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Attackers might perform multiple small transfers to match normal egress activity in the network, to evade detection. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
A machine learning job found an unusually large spike in successful authentication events from a particular source IP address. This can be due to password spraying, user enumeration or brute force activity. |
[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access], [Tactic: Defense Evasion], [Resources: Investigation Guide] |
None |
105 |
|
Identifies files written or modified in the startup folder by unsigned processes. Adversaries may abuse this technique to maintain persistence in an environment. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
109 |
|
Identifies files written to or modified in the startup folder by commonly abused processes. Adversaries may use this technique to maintain persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Identifies run key or startup key registry modifications. In order to survive reboots and other system interrupts, attackers will modify run keys within the registry or leverage startup folder items as a form of persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
113 |
|
Detects the modification of Group Policy Objects (GPO) to add a startup/logon script to users or computer objects. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
111 |
|
A statistical model has identified command-and-control (C2) beaconing activity. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network. |
[Domain: Network], [Use Case: C2 Beaconing Detection], [Tactic: Command and Control] |
None |
6 |
|
Statistical Model Detected C2 Beaconing Activity with High Confidence |
A statistical model has identified command-and-control (C2) beaconing activity with high confidence. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network. |
[Domain: Network], [Use Case: C2 Beaconing Detection], [Tactic: Command and Control] |
None |
5 |
Stolen Credentials Used to Login to Okta Account After MFA Reset |
Detects a sequence of suspicious activities on Windows hosts indicative of credential compromise, followed by efforts to undermine multi-factor authentication (MFA) and single sign-on (SSO) mechanisms for an Okta user account. |
[Tactic: Persistence], [Use Case: Identity and Access Audit], [Data Source: Okta], [Data Source: Elastic Defend], [Rule Type: Higher-Order Rule], [Domain: Endpoint], [Domain: Cloud] |
None |
4 |
Adversaries may create or modify the Sublime application plugins or scripts to execute a malicious payload each time the Sublime application is started. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
108 |
|
Detects successful single sign-on (SSO) events to Okta applications from an unrecognized or "unknown" client device, as identified by the user-agent string. This activity may be indicative of exploitation of a vulnerability in Okta’s Classic Engine, which could allow an attacker to bypass application-specific sign-on policies, such as device or network restrictions. The vulnerability potentially enables unauthorized access to applications using only valid, stolen credentials, without requiring additional authentication factors. |
[Domain: SaaS], [Data Source: Okta], [Use Case: Threat Detection], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |
None |
3 |
|
This rule monitors for the usage of the sudo -l command, which is used to list the allowed and forbidden commands for the invoking user. Attackers may execute this command to enumerate commands allowed to be executed with sudo permissions, potentially allowing to escalate privileges to root. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |
None |
6 |
|
Identifies the attempted use of a heap-based buffer overflow vulnerability for the Sudo binary in Unix-like systems (CVE-2021-3156). Successful exploitation allows an unprivileged user to escalate to the root user. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
104 |
|
A sudoers file specifies the commands that users or groups can run and from which terminals. Adversaries can take advantage of these configurations to execute commands as other users or spawn processes with higher privileges. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
205 |
|
Identifies executions of .NET compilers with suspicious parent processes, which can indicate an attacker’s attempt to compile code after delivery in order to bypass security mechanisms. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
211 |
|
Detects the use of Reflection.Assembly to load PEs and DLLs in memory in PowerShell scripts. Attackers use this method to load executables and DLLs without writing to the disk, bypassing security solutions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
8.12.0 |
216 |
|
Monitors for /proc//maps file reads. The /proc//maps file in Linux provides a memory map for a specific process, detailing the memory segments, permissions, and what files are mapped to these segments. Attackers may read a process’s memory map to identify memory addresses for code injection or process hijacking. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |
None |
2 |
|
Detects suspicious process events executed by the APT package manager, potentially indicating persistence through an APT backdoor. In Linux, APT (Advanced Package Tool) is a command-line utility used for handling packages on Debian-based systems, providing functions for installing, updating, upgrading, and removing software along with managing package repositories. Attackers can backdoor APT to gain persistence by injecting malicious code into scripts that APT runs, thereby ensuring continued unauthorized access or control each time APT is used for package management. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
4 |
|
Detects suspicious network events executed by the APT package manager, potentially indicating persistence through an APT backdoor. In Linux, APT (Advanced Package Tool) is a command-line utility used for handling packages on Debian-based systems, providing functions for installing, updating, upgrading, and removing software along with managing package repositories. Attackers can backdoor APT to gain persistence by injecting malicious code into scripts that APT runs, thereby ensuring continued unauthorized access or control each time APT is used for package management. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Command and Control], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
4 |
|
Identify read access to a high number of Active Directory object attributes. The knowledge of objects properties can help adversaries find vulnerabilities, elevate privileges or collect sensitive information. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: System], [Data Source: Active Directory], [Data Source: Windows] |
None |
2 |
|
Detects when a user reports suspicious activity for their Okta account. These events should be investigated, as they can help security teams identify when an adversary is attempting to gain access to their network. |
[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Initial Access] |
None |
208 |
|
Identifies the creation of the Antimalware Scan Interface (AMSI) DLL in an unusual location. This may indicate an attempt to bypass AMSI by loading a rogue AMSI module instead of the legit one. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
213 |
|
Identifies the execution of the Automator Workflows process followed by a network connection from it’s XPC service. Adversaries may drop a custom workflow template that hosts malicious JavaScript for Automation (JXA) code as an alternative to using osascript. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies the execution of a suspicious browser child process. Adversaries may gain access to a system through a user visiting a website over the normal course of browsing. With this technique, the user’s web browser is typically targeted for exploitation. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies suspicious modifications of the calendar file by an unusual process. Adversaries may create a custom calendar notification procedure to execute a malicious program at a recurring interval to establish persistence. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies suspicious commands being used with certutil.exe. CertUtil is a native Windows component which is part of Certificate Services. CertUtil is often abused by attackers to live off the land for stealthier command and control or data exfiltration. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Suspicious Child Process of Adobe Acrobat Reader Update Service |
Detects attempts to exploit privilege escalation vulnerabilities related to the Adobe Acrobat Reader PrivilegedHelperTool responsible for installing updates. For more information, refer to CVE-2020-9615, CVE-2020-9614 and CVE-2020-9613 and verify that the impacted system is patched. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
106 |
Identifies suspicious command execution (cmd) via Windows Management Instrumentation (WMI) on a remote host. This could be indicative of adversary lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Identifies suspicious child processes of communications apps, which can indicate a potential masquerading as the communication app or the exploitation of a vulnerability on the application causing it to execute code. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
5 |
|
Identifies when suspicious content is extracted from a file and subsequently decompressed using the funzip utility. Malware may execute the tail utility using the "-c" option to read a sequence of bytes from the end of a file. The output from tail can be piped to funzip in order to decompress malicious code before it is executed. This behavior is consistent with malware families such as Bundlore. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
5 |
|
Identifies attempts to create or modify a crontab via a process that is not crontab (i.e python, osascript, etc.). This activity should not be highly prevalent and could indicate the use of cron as a persistence mechanism by a threat actor. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
106 |
|
Suspicious DLL Loaded for Persistence or Privilege Escalation |
Identifies the loading of a non Microsoft signed DLL that is missing on a default Windows install (phantom DLL) or one that can be loaded from a different location by a native Windows process. This may be abused to persist or elevate privileges via privileged file write vulnerabilities. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
113 |
Identifies when the openssl command-line utility is used to encrypt multiple files on a host within a short time window. Adversaries may encrypt data on a single or multiple systems in order to disrupt the availability of their target’s data and may attempt to hold the organization’s data to ransom for the purposes of extortion. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend] |
None |
6 |
|
Monitors for dynamic linker discovery via the od utility. od (octal dump) is a command-line utility in Unix operating systems used for displaying data in various formats, including octal, hexadecimal, decimal, and ASCII, primarily used for examining and debugging binary files or data streams. Attackers can leverage od to analyze the dynamic linker by identifying injection points and craft exploits based on the observed behaviors and structures within these files. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
2 |
|
Identifies the execution of a suspicious child process of the Event Monitor Daemon (emond). Adversaries may abuse this service by writing a rule to execute commands when a defined event occurs, such as system start up or user authentication. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
107 |
|
A suspicious Endpoint Security parent process was detected. This may indicate a process hollowing or other form of code injection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
This detection rule addresses multiple vulnerabilities in the CUPS printing system, including CVE-2024-47176, CVE-2024-47076, CVE-2024-47175, and CVE-2024-47177. Specifically, this rule detects suspicious process command lines executed by child processes of foomatic-rip and cupsd. These flaws impact components like cups-browsed, libcupsfilters, libppd, and foomatic-rip, allowing remote unauthenticated attackers to manipulate IPP URLs or inject malicious data through crafted UDP packets or network spoofing. This can result in arbitrary command execution when a print job is initiated. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Use Case: Vulnerability], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies the execution of a process with arguments pointing to the INetCache Folder. Adversaries may deliver malicious content via WININET during initial access. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
103 |
|
Identifies when a script interpreter or signed binary is launched via a non-standard working directory. An attacker may use this technique to evade defenses. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Identifies suspicious execution of the built-in Windows Installer, msiexec.exe, to install a package from usual paths or parent process. Adversaries may abuse msiexec.exe to launch malicious local MSI files. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
3 |
|
Identifies execution of common Microsoft Office applications to launch an Office Add-In from a suspicious path or with an unusual parent process. This may indicate an attempt to get initial access via a malicious phishing MS Office Add-In. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
105 |
|
Identifies execution of a suspicious program via scheduled tasks by looking at process lineage and command line usage. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
109 |
|
Detects Linux Bash commands from the the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
107 |
|
Identifies a suspicious Windows explorer child process. Explorer.exe can be abused to launch malicious scripts or executables from a trusted parent process. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Detects the manual creation of files in specific etc directories, via user root, used by Linux malware to persist and elevate privileges on compromised systems. File creation in these directories should not be entirely common and could indicate a malicious binary or script installing persistence mechanisms for long term access. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Orbit], [Threat: Lightning Framework], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
116 |
|
This rule monitors for a file creation event originating from a kworker parent process. kworker, or kernel worker, processes are part of the kernel’s workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
5 |
|
Identifies suspicious file download activity from a Google Drive URL. This could indicate an attempt to deliver phishing payloads via a trusted webservice. |
[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: System] |
None |
4 |
|
Identifies an incoming SMB connection followed by a suspicious file rename operation. This may indicate a remote ransomware attack via the SMB protocol. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies the execution of a browser process to open an HTML file with high entropy and size. Adversaries may smuggle data and files past content filters by hiding malicious payloads inside of seemingly benign HTML files. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Defend] |
None |
108 |
|
Identifies the execution of a launchd child process with a hidden file. An adversary can establish persistence by installing a new logon item, launch agent, or daemon that executes upon login. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
106 |
|
Identifies a suspicious image load (taskschd.dll) from Microsoft Office processes. This behavior may indicate adversarial activity where a scheduled task is configured via Windows Component Object Model (COM). This technique can be used to configure persistence and evade monitoring by avoiding the usage of the traditional Windows binary (schtasks.exe) used to manage scheduled tasks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
109 |
|
Identifies the creation of a suspicious ImagePath value. This could be an indication of an adversary attempting to stealthily persist or escalate privileges through abnormal service creation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Detects Inter-Process Communication with Outlook via Component Object Model from an unusual process. Adversaries may target user email to collect sensitive information or send email on their behalf via API. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend] |
None |
7 |
|
Suspicious Interactive Shell Spawned From Inside A Container |
This rule detects when an interactive shell is spawned inside a running container. This could indicate a potential container breakout attempt or an attacker’s attempt to gain unauthorized access to the underlying host. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |
None |
2 |
Identifies suspicious processes being spawned by the JetBrain TeamCity process. This activity could be related to JetBrains remote code execution vulnerabilities. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: System], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
103 |
|
Monitors for the elevation of regular user permissions to root permissions through the kworker process. kworker, or kernel worker, processes are part of the kernel’s workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process, and hijack the execution flow by hooking certain functions/syscalls through a rootkit in order to provide easy access to root via a special modified command. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
2 |
|
Identifies suspicious access to LSASS handle from a call trace pointing to seclogon.dll and with a suspicious access rights value. This may indicate an attempt to leak an LSASS handle via abusing the Secondary Logon service in preparation for credential access. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |
None |
208 |
|
Identifies access attempts to LSASS handle, this may indicate an attempt to dump credentials from Lsass memory. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |
None |
107 |
|
Identifies suspicious child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, Excel). These child processes are often launched during exploitation of Office applications or from documents with malicious macros. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Identifies suspicious child processes of Microsoft Outlook. These child processes are often associated with spear phishing activity. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
8.13.0 |
315 |
|
Identifies a suspicious managed code hosting process which could indicate code injection or other form of suspicious code execution. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Elastic Endgame] |
8.13.0 |
208 |
|
Monitors for grep activity related to memory mapping. The /proc/*/maps file in Linux provides a memory map for a specific process, detailing the memory segments, permissions, and what files are mapped to these segments. Attackers may read a process’s memory map to identify memory addresses for code injection or process hijacking. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
3 |
|
Identifies when a Microsoft 365 Mailbox is accessed by a ClientAppId that was observed for the fist time during the last 10 days. |
[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |
None |
107 |
|
Identifies potential abuse of the Microsoft Diagnostics Troubleshooting Wizard (MSDT) to proxy malicious command or binary execution via malicious process arguments. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon] |
None |
110 |
|
Identifies service creation events of common mining services, possibly indicating the infection of a system with a cryptominer. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
6 |
|
Detects file events involving kernel modules in modprobe configuration files, which may indicate unauthorized access or manipulation of critical kernel modules. Attackers may tamper with the modprobe files to load malicious or unauthorized kernel modules, potentially bypassing security measures, escalating privileges, or hiding their activities within the system. |
[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |
None |
108 |
|
Identifies LSASS loading an unsigned or untrusted DLL. Windows Security Support Provider (SSP) DLLs are loaded into LSSAS process at system start. Once loaded into the LSA, SSP DLLs have access to encrypted and plaintext passwords that are stored in Windows, such as any logged-on user’s Domain password or smart card PINs. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
9 |
|
Suspicious Network Activity to the Internet by Previously Unknown Executable |
This rule monitors for network connectivity to the internet from a previously unknown executable located in a suspicious directory. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to establish connections to unknown or suspicious destinations such as a command and control server. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
11 |
Detects suspicious network events executed by systemd, potentially indicating persistence through a systemd backdoor. Systemd is a system and service manager for Linux operating systems, used to initialize and manage system processes. Attackers can backdoor systemd for persistence by creating or modifying systemd unit files to execute malicious scripts or commands, or by replacing legitimate systemd binaries with compromised ones, ensuring that their malicious code is automatically executed at system startup or during certain system events. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Command and Control], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
3 |
|
This rule detects commonly abused network utilities running inside a container. Network utilities like nc, nmap, dig, tcpdump, ngrep, telnet, mitmproxy, zmap can be used for malicious purposes such as network reconnaissance, monitoring, or exploitation, and should be monitored closely within a container. |
[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Command and Control], [Tactic: Reconnaissance] |
None |
2 |
|
Identifies suspicious child processes of PDF reader applications. These child processes are often launched via exploitation of PDF applications or social engineering. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Initial Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Monitors for the generation of a passwd password entry via openssl, followed by a file write activity on the "/etc/passwd" file. The "/etc/passwd" file in Linux stores user account information, including usernames, user IDs, group IDs, home directories, and default shell paths. Attackers may exploit a misconfiguration in the "/etc/passwd" file permissions or other privileges to add a new entry to the "/etc/passwd" file with root permissions, and leverage this new user account to login as root. |
[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
3 |
|
Detects the presence of a portable executable (PE) in a PowerShell script by looking for its encoded header. Attackers embed PEs into PowerShell scripts to inject them into memory, avoiding defences by not writing to disk. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |
None |
112 |
|
Identifies the PowerShell engine being invoked by unexpected processes. Rather than executing PowerShell functionality with powershell.exe, some attackers do this to operate more stealthily. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
211 |
|
Identifies suspicious PowerShell execution spawning from Windows Script Host processes (cscript or wscript.exe). |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: System], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
101 |
|
A machine learning job detected a PowerShell script with unusual data characteristics, such as obfuscation, that may be a characteristic of malicious PowerShell script text blocks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Execution] |
None |
107 |
|
Detects deletion of print driver files by an unusual process. This may indicate a clean up attempt post successful privilege escalation via Print Spooler service related vulnerabilities. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
207 |
|
Detects attempts to exploit a privilege escalation vulnerability (CVE-2020-1030) related to the print spooler service. Exploitation involves chaining multiple primitives to load an arbitrary DLL into the print spooler process running as SYSTEM. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Detects attempts to exploit privilege escalation vulnerabilities related to the Print Spooler service including CVE-2020-1048 and CVE-2020-1337. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint] |
None |
113 |
|
Detects attempts to exploit privilege escalation vulnerabilities related to the Print Spooler service. For more information refer to the following CVE’s - CVE-2020-1048, CVE-2020-1337 and CVE-2020-1300 and verify that the impacted system is patched. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
214 |
|
This rule monitors for a rapid enumeration of 25 different proc cmd, stat, and exe files, which suggests an abnormal activity pattern. Such behavior could be an indicator of a malicious process scanning or gathering information about running processes, potentially for reconnaissance, privilege escalation, or identifying vulnerable targets. |
[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |
None |
7 |
|
Identifies suspicious process access events from an unknown memory region. Endpoint security solutions usually hook userland Windows APIs in order to decide if the code that is being executed is malicious or not. It’s possible to bypass hooked functions by writing malicious functions that call syscalls directly. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Sysmon] |
None |
211 |
|
Identifies when a process is created and immediately accessed from an unknown memory code region and by the same parent process. This may indicate a code injection attempt. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Sysmon] |
None |
208 |
|
Identifies suspicious psexec activity which is executing from the psexec service that has been renamed, possibly to evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
112 |
|
Identifies suspicious Image Loading of the Remote Desktop Services ActiveX Client (mstscax), this may indicate the presence of RDP lateral movement capability. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
110 |
|
Identifies remote access to the registry using an account with Backup Operators group membership. This may indicate an attempt to exfiltrate credentials by dumping the Security Account Manager (SAM) registry hive in preparation for credential access and privileges elevation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Credential Access], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Data Source: System] |
None |
111 |
|
Identifies instances where VMware-related files, such as those with extensions like ".vmdk", ".vmx", ".vmxf", ".vmsd", ".vmsn", ".vswp", ".vmss", ".nvram", and ".vmem", are renamed on a Linux system. The rule monitors for the "rename" event action associated with these file types, which could indicate malicious activity. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
6 |
|
Identifies instances where the "index.html" file within the "/usr/lib/vmware/*" directory is renamed on a Linux system. The rule monitors for the "rename" event action associated with this specific file and path, which could indicate malicious activity. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
6 |
|
Identifies suspicious processes being spawned by the ScreenConnect client processes. This activity may indicate execution abusing unauthorized access to the ScreenConnect remote access software. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
8.13.0 |
206 |
|
Identifies scrobj.dll loaded into unusual Microsoft processes. This usually means a malicious scriptlet is being executed in the target process. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Sysmon] |
None |
109 |
|
Identifies the creation of a new Windows service with suspicious Service command values. Windows services typically run as SYSTEM and can be used for privilege escalation and persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: System] |
None |
10 |
|
A suspicious SolarWinds child process was detected, which may indicate an attempt to execute malicious programs. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies suspicious startup shell folder modifications to change the default Startup directory in order to bypass detections monitoring file creation in the Windows Startup folder. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Identifies the creation of a symbolic link to a suspicious file or location. A symbolic link is a reference to a file or directory that acts as a pointer or shortcut, allowing users to access the target file or directory from a different location in the file system. An attacker can potentially leverage symbolic links for privilege escalation by tricking a privileged process into following the symbolic link to a sensitive file, giving the attacker access to data or capabilities they would not normally have. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
6 |
|
Monitors file events on sysctl configuration files (e.g., /etc/sysctl.conf, /etc/sysctl.d/*.conf) to identify potential unauthorized access or manipulation of system-level configuration settings. Attackers may tamper with the sysctl configuration files to modify kernel parameters, potentially compromising system stability, performance, or security. |
[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |
None |
108 |
|
Suspicious System Commands Executed by Previously Unknown Executable |
This rule monitors for the execution of several commonly used system commands executed by a previously unknown executable located in commonly abused directories. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to run malicious code. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
107 |
Identifies instances where VMware processes, such as "vmware-vmx" or "vmx," are terminated on a Linux system by a "kill" command. The rule monitors for the "end" event type, which signifies the termination of a process. The presence of a "kill" command as the parent process for terminating VMware processes may indicate that a threat actor is attempting to interfere with the virtualized environment on the targeted system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
6 |
|
Identifies the execution of the Microsoft Diagnostic Wizard to open a diagcab file from a suspicious path and with an unusual parent process. This may indicate an attempt to execute malicious Troubleshooting Pack Cabinet files. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: System] |
None |
4 |
|
This rule monitors for the execution of suspicious linux tools through ProxyChains. ProxyChains is a command-line tool that enables the routing of network connections through intermediary proxies, enhancing anonymity and enabling access to restricted resources. Attackers can exploit the ProxyChains utility to hide their true source IP address, evade detection, and perform malicious activities through a chain of proxy servers, potentially masking their identity and intentions. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
7 |
|
Detects the creation of a WMI Event Subscription. Attackers can abuse this mechanism for persistence or to elevate to SYSTEM privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Sysmon] |
None |
106 |
|
Identifies a suspicious image load (wmiutils.dll) from Microsoft Office processes. This behavior may indicate adversarial activity where child processes are spawned via Windows Management Instrumentation (WMI). This technique can be used to execute code and evade traditional parent/child processes spawned from Microsoft Office products. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
Identifies WMIC allowlist bypass techniques by alerting on suspicious execution of scripts. When WMIC loads scripting libraries it may be indicative of an allowlist bypass. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
109 |
|
Identifies the access or file open of web browser sensitive files by an untrusted/unsigned process or osascript. Adversaries may acquire credentials from web browsers by reading files specific to the target browser. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
209 |
|
A suspicious WerFault child process was detected, which may indicate an attempt to run via the SilentProcessExit registry key manipulation. Verify process details such as command line, network connections and file writes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
315 |
|
Identifies the execution of the Windows Command Shell process (cmd.exe) with suspicious argument values. This behavior is often observed during malware installation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: System], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
101 |
|
Identifies the execution of PowerShell with suspicious argument values. This behavior is often observed during malware installation leveraging PowerShell. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: System], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
101 |
|
A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same host name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |
[Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |
None |
7 |
|
Suspicious Windows Process Cluster Spawned by a Parent Process |
A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same parent process name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |
[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |
None |
7 |
A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same user name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |
[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |
None |
7 |
|
A suspicious Zoom child process was detected, which may indicate an attempt to run unnoticed. Verify process details such as command line, network connections, file writes and associated file signature details as well. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
8.13.0 |
315 |
|
Identifies suspicious child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, and Excel). These child processes are often launched during exploitation of Office applications or by documents with malicious macros. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Defend] |
None |
207 |
|
Identifies a high volume of |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Jamf Protect], [Data Source: Elastic Defend] |
8.12.0 |
1 |
|
This rule monitors the syslog log file for error messages related to the rc.local process. The rc.local file is a script that is executed during the boot process on Linux systems. Attackers may attempt to modify the rc.local file to execute malicious commands or scripts during system startup. This rule detects error messages such as "Connection refused," "No such file or directory," or "command not found" in the syslog log file, which may indicate that the rc.local file has been tampered with. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence] |
None |
2 |
|
This rule monitors for the usage of the which command with an unusual amount of process arguments. Attackers may leverage the which command to enumerate the system for useful installed utilities that may be used after compromising a system to escalate privileges or move latteraly across the network. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
7 |
|
Identifies a suspicious parent child process relationship with cmd.exe descending from svchost.exe |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
318 |
|
Identifies the creation of symbolic links to a shadow copy. Symbolic links can be used to access files in the shadow copy, including sensitive files such as ntds.dit, System Boot Key and browser offline credentials. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
This rule monitors for the copying or moving of a system binary. Adversaries may copy/move and rename system binaries to evade detection. Copying a system binary to a different location should not occur often, so if it does, the activity should be investigated. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
13 |
|
Identifies the use of built-in tools to read the contents of \etc\hosts on a local machine. Attackers may use this data to discover remote machines in an environment that may be used for Lateral Movement from the current system. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
Identifies the execution of discovery commands to enumerate system information, files, and folders using the Windows Command Shell. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame], [Data Source: System] |
None |
14 |
|
Identifies the deletion of sensitive Linux system logs. This may indicate an attempt to evade detection or destroy forensic evidence on a system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
112 |
|
Adversaries may attempt to get a listing of network connections to or from a compromised system. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
Identifies the use of built-in tools which adversaries may use to enumerate the system owner/user of a compromised system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
Detects the usage of commonly used system service discovery techniques, which attackers may use during the reconnaissance phase after compromising a system in order to gain a better understanding of the environment and/or escalate privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR], [Data Source: System] |
None |
9 |
|
Windows services typically run as SYSTEM and can be used as a privilege escalation opportunity. Malware or penetration testers may run a shell as a service to gain SYSTEM permissions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
8.13.0 |
314 |
|
Detects the usage of commonly used system time discovery techniques, which attackers may use during the reconnaissance phase after compromising a system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR], [Data Source: System] |
None |
10 |
|
Files that are placed in the /etc/init.d/ directory in Unix can be used to start custom applications, services, scripts or commands during start-up. Init.d has been mostly replaced in favor of Systemd. However, the "systemd-sysv-generator" can convert init.d files to service unit files that run at boot. Adversaries may add or alter files located in the /etc/init.d/ directory to execute malicious code upon boot in order to gain persistence on the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
13 |
|
Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features, including Wi-Fi and website passwords, secure notes, certificates, and Kerberos. Adversaries may collect the keychain storage data from a system to acquire credentials. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
206 |
|
This rule detects the creation of a systemd generator file. Generators are small executables executed by systemd at bootup and during configuration reloads. Their main role is to convert non-native configuration and execution parameters into dynamically generated unit files, symlinks, or drop-ins, extending the unit file hierarchy for the service manager. Systemd generators can be used to execute arbitrary code at boot time, which can be leveraged by attackers to maintain persistence on a Linux system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
3 |
|
This rule detects the creation or renaming of a new Systemd file in all of the common Systemd service locations for both root and regular users. Systemd service files are configuration files in Linux systems used to define and manage system services. Malicious actors can leverage systemd service files to achieve persistence by creating or modifying services to execute malicious commands or payloads during system startup or at a predefined interval by adding a systemd timer. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
15 |
|
Systemctl is a process used in Linux systems to manage systemd processes through service configuration files. Malicious actors can leverage systemd services to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |
None |
3 |
|
Detects the creation of a systemd timer within any of the default systemd timer directories. Systemd timers can be used by an attacker to gain persistence, by scheduling the execution of a command or script. Similarly to cron/at, systemd timers can be set up to execute on boot time, or on a specific point in time, which allows attackers to regain access in case the connection to the infected asset was lost. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
15 |
|
Monitors for the creation of rule files that are used by systemd-udevd to manage device nodes and handle kernel device events in the Linux operating system. Systemd-udevd can be exploited for persistence by adversaries by creating malicious udev rules that trigger on specific events, executing arbitrary commands or payloads whenever a certain device is plugged in or recognized by the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
7 |
|
Identifies the use of the mount_apfs command to mount the entire file system through Apple File System (APFS) snapshots as read-only and with the noowners flag set. This action enables the adversary to access almost any file in the file system, including all user data and files protected by Apple’s privacy framework (TCC). |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Use Case: Vulnerability], [Data Source: Elastic Defend] |
None |
106 |
|
This rule monitors the syslog log file for messages related to instances of a tainted kernel module load. Rootkits often leverage kernel modules as their main defense evasion technique. Detecting tainted kernel module loads is crucial for ensuring system security and integrity, as malicious or unauthorized modules can compromise the kernel and lead to system vulnerabilities or unauthorized access. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |
None |
4 |
|
This rule monitors the syslog log file for messages related to instances of a out-of-tree kernel module load, indicating the taining of the kernel. Rootkits often leverage kernel modules as their main defense evasion technique. Detecting tainted kernel module loads is crucial for ensuring system security and integrity, as malicious or unauthorized modules can compromise the kernel and lead to system vulnerabilities or unauthorized access. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |
None |
2 |
|
Adversaries may attempt to clear or disable the Bash command-line history in an attempt to evade detection or forensic investigations. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
107 |
|
Indicates the creation and deletion of a scheduled task within a short time interval. Adversaries can use these to proxy malicious execution via the schedule service and perform clean up. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: System] |
None |
8 |
|
Identifies the deletion of backup files, saved using third-party software, by a process outside of the backup suite. Adversaries may delete Backup files to ensure that recovery from a ransomware attack is less likely. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
This rule is triggered when a hash indicator from the Threat Intel Filebeat module or integrations has a match against an event that contains file hashes, such as antivirus alerts, process creation, library load, and file operation events. |
[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Threat Match] |
None |
8 |
|
This rule is triggered when an IP address indicator from the Threat Intel Filebeat module or integrations has a match against a network event. |
[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Threat Match] |
None |
7 |
|
This rule is triggered when a URL indicator from the Threat Intel Filebeat module or integrations has a match against an event that contains URL data, like DNS events, network logs, etc. |
[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Threat Match] |
None |
7 |
|
This rule is triggered when a Windows registry indicator from the Threat Intel Filebeat module or integrations has a match against an event that contains registry data. |
[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Threat Match] |
None |
7 |
|
Timestomping is an anti-forensics technique which is used to modify the timestamps of a file, often to mimic files that are in the same folder. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
106 |
|
Identify activity related where adversaries can include a trap command which then allows programs and shells to specify commands that will be executed upon receiving interrupt signals. |
[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
2 |
|
UAC Bypass Attempt via Elevated COM Internet Explorer Add-On Installer |
Identifies User Account Control (UAC) bypass attempts by abusing an elevated COM Interface to launch a malicious program. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
UAC Bypass Attempt via Privileged IFileOperation COM Interface |
Identifies attempts to bypass User Account Control (UAC) via DLL side-loading. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
Identifies an attempt to bypass User Account Control (UAC) by masquerading as a Microsoft trusted Windows directory. Attackers may bypass UAC to stealthily execute code with elevated permissions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
214 |
|
UAC Bypass Attempt with IEditionUpgradeManager Elevated COM Interface |
Identifies attempts to bypass User Account Control (UAC) by abusing an elevated COM Interface to launch a rogue Windows ClipUp program. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
Identifies User Account Control (UAC) bypass via hijacking DiskCleanup Scheduled Task. Attackers bypass UAC to stealthily execute code with elevated permissions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies User Account Control (UAC) bypass attempts via the ICMLuaUtil Elevated COM interface. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
110 |
|
Identifies attempts to bypass User Account Control (UAC) by hijacking the Microsoft Management Console (MMC) Windows Firewall snap-in. Attackers bypass UAC to stealthily execute code with elevated permissions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Monitors for the elevation of regular user permissions to root permissions through a previously unknown executable. Attackers may attempt to evade detection by hijacking the execution flow and hooking certain functions/syscalls through a rootkit in order to provide easy access to root via a special modified command. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
4 |
|
Identifies unauthorized access attempts to Okta applications. |
[Tactic: Initial Access], [Use Case: Identity and Access Audit], [Data Source: Okta] |
None |
209 |
|
Unauthorized Scope for Public App OAuth2 Token Grant with Client Credentials |
Identifies a failed OAuth 2.0 token grant attempt for a public client app using client credentials. This event is generated when a public client app attempts to exchange a client credentials grant for an OAuth 2.0 access token, but the request is denied due to the lack of required scopes. This could indicate compromised client credentials in which an adversary is attempting to obtain an access token for unauthorized scopes. This is a [New Terms](https://www.elastic.co/guide/en/security/master/rules-ui-create.html#create-new-terms-rule) rule where the |
[Domain: SaaS], [Data Source: Okta], [Use Case: Threat Detection], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |
None |
4 |
Detects changes to registry persistence keys that are not commonly used or modified by legitimate programs. This could be an indication of an adversary’s attempt to persist in a stealthy manner. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
111 |
|
Identifies when a child process is spawned by the screensaver engine process, which is consistent with an attacker’s malicious payload being executed after the screensaver activated on the endpoint. An adversary can maintain persistence on a macOS endpoint by creating a malicious screensaver (.saver) file and configuring the screensaver plist file to execute code each time the screensaver is activated. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
107 |
|
This rule monitors for inter-process communication via Unix sockets. Adversaries may attempt to communicate with local Unix sockets to enumerate application details, find vulnerabilities/configuration mistakes and potentially escalate privileges or set up malicious communication channels via Unix sockets for inter-process communication to attempt to evade detection. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |
None |
3 |
|
Monitors for the execution of a previously unknown unix binary with read, write and execute memory region permissions. The mprotect() system call is used to change the access protections on a region of memory that has already been allocated. This syscall allows a process to modify the permissions of pages in its virtual address space, enabling or disabling permissions such as read, write, and execute for those pages. RWX permissions on memory is in many cases overly permissive, and should be analyzed thoroughly. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Auditd Manager] |
None |
3 |
|
Identifies an unsigned Windows Background Intelligent Transfer Service (BITS) client process. Attackers may abuse BITS functionality to download or upload data using the BITS service. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
3 |
|
Identifies an unsigned library created in the last 5 minutes and subsequently loaded by a shared windows service (svchost). Adversaries may use this technique to maintain persistence or run with System privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
7 |
|
Identifies digitally signed (trusted) processes loading unsigned DLLs. Attackers may plant their payloads into the application folder and invoke the legitimate application to execute the payload, masking actions they perform under a legitimate, trusted, and potentially elevated system or software process. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
102 |
|
Identifies a Windows trusted program running from locations often abused by adversaries to masquerade as a trusted program and loading a recently dropped DLL. This behavior may indicate an attempt to evade defenses via side-loading a malicious DLL within the memory space of a signed processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
9 |
|
Identifies unusual DLLs loaded by the DNS Server process, potentially indicating the abuse of the ServerLevelPluginDll functionality. This can lead to privilege escalation and remote code execution with SYSTEM privileges. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
3 |
|
Identifies the load of a DLL without a valid code signature by the Azure AD Sync process, which may indicate an attempt to persist or collect sensitive credentials passing through the Azure AD synchronization server. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
1 |
|
Identifies attempt to load an untrusted driver. Adversaries may modify code signing policies to enable execution of unsigned or self-signed code. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
9 |
|
A machine learning job detected an AWS API command that, while not inherently suspicious or abnormal, is being made by a user context that does not normally use the command. This can be the result of compromised credentials or keys as someone uses a valid account to persist, move laterally, or exfiltrate data. |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |
None |
209 |
|
Identifies a suspicious child process of the Windows virtual system process, which could indicate code injection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies an unexpected process spawning from dns.exe, the process responsible for Windows DNS server services, which may indicate activity related to remote code execution or other forms of exploitation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies child processes of unusual instances of RunDLL32 where the command line parameters were suspicious. Misuse of RunDLL32 could indicate malicious activity. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
A machine learning job detected AWS command activity that, while not inherently suspicious or abnormal, is sourcing from a geolocation (city) that is unusual for the command. This can be the result of compromised credentials or keys being used by a threat actor in a different geography than the authorized user(s). |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |
None |
209 |
|
A machine learning job detected AWS command activity that, while not inherently suspicious or abnormal, is sourcing from a geolocation (country) that is unusual for the command. This can be the result of compromised credentials or keys being used by a threat actor in a different geography than the authorized user(s). |
[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |
None |
209 |
|
A machine learning job detected a rare and unusual DNS query that indicate network activity with unusual DNS domains. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from an uncommon domain. When malware is already running, it may send requests to an uncommon DNS domain the malware uses for command-and-control communication. |
[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |
None |
104 |
|
This rule detects the execution of the DPKG command by processes not associated with the DPKG package manager. The DPKG command is used to install, remove, and manage Debian packages on a Linux system. Attackers can abuse the DPKG command to install malicious packages on a system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |
None |
2 |
|
This rule leverages alert data from various Discovery building block rules to alert on signals with unusual unique host.id and user.id entries. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: Higher-Order Rule], [Rule Type: BBR] |
None |
2 |
|
Unusual Discovery Signal Alert with Unusual Process Command Line |
This rule leverages alert data from various Discovery building block rules to alert on signals with unusual unique host.id, user.id and process.command_line entries. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: Higher-Order Rule] |
None |
1 |
Unusual Discovery Signal Alert with Unusual Process Executable |
This rule leverages Discovery building block rule alert data to alert on signals with unusual unique host.id, user.id and process.executable entries. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: Higher-Order Rule] |
None |
2 |
Unusual Executable File Creation by a System Critical Process |
Identifies an unexpected executable file being created or modified by a Windows system critical process, which may indicate activity related to remote code execution or other forms of exploitation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
211 |
Identifies the execution of a child process from a Microsoft Common Console file. Adversaries may embed a malicious command in an MSC file in order to trick victims into executing malicious commands. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Initial Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
101 |
|
Identifies suspicious creation of Alternate Data Streams on highly targeted files. This is uncommon for legitimate files and sometimes done by adversaries to hide malware. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Elastic Endgame] |
8.13.0 |
215 |
|
Identifies an unexpected file being modified by dns.exe, the process responsible for Windows DNS Server services, which may indicate activity related to remote code execution or other forms of exploitation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
111 |
|
Detects repeated high-confidence BLOCKED actions coupled with specific violation codes such as MISCONDUCT, indicating persistent misuse or attempts to probe the model’s ethical boundaries. |
[Domain: LLM], [Data Source: AWS Bedrock], [Data Source: AWS S3], [Use Case: Policy Violation], [Mitre Atlas: T0051], [Mitre Atlas: T0054] |
8.13.0 |
4 |
|
A machine learning job detected a user logging in at a time of day that is unusual for the user. This can be due to credentialed access via a compromised account when the user and the threat actor are in different time zones. In addition, unauthorized user activity often takes place during non-business hours. |
[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access], [Resources: Investigation Guide] |
None |
105 |
|
This rule identifies potentially malicious processes attempting to access the cloud service provider’s instance metadata service (IMDS) API endpoint, which can be used to retrieve sensitive instance-specific information such as instance ID, public IP address, and even temporary security credentials if role’s are assumed by that instance. The rule monitors for various tools and scripts like curl, wget, python, and perl that might be used to interact with the metadata API. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Discovery], [Data Source: Elastic Defend] |
None |
2 |
|
This rule detects interactive shells launched from system users. System users typically do not require interactive shells, and their presence may indicate malicious activity. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
1 |
|
Identifies Linux processes that do not usually use the network but have unexpected network activity, which can indicate command-and-control, lateral movement, persistence, or data exfiltration activity. A process with unusual network activity can denote process exploitation or injection, where the process is used to run persistence mechanisms that allow a malicious actor remote access or control of the host, data exfiltration, and execution of unauthorized network applications. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |
None |
104 |
|
Looks for commands related to system network configuration discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network configuration discovery in order to increase their understanding of connected networks and hosts. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |
None |
105 |
|
Looks for commands related to system network connection discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network connection discovery in order to increase their understanding of connected services and systems. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |
None |
104 |
|
Identifies unusual destination port activity that can indicate command-and-control, persistence mechanism, or data exfiltration activity. Rarely used destination port activity is generally unusual in Linux fleets, and can indicate unauthorized access or threat actor activity. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |
None |
104 |
|
Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |
None |
104 |
|
Looks for commands related to system process discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system process discovery in order to increase their understanding of software applications running on a target host or network. This may be a precursor to selection of a persistence mechanism or a method of privilege elevation. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |
None |
104 |
|
Looks for commands related to system information discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system information discovery in order to gather detailed information about system configuration and software versions. This may be a precursor to selection of a persistence mechanism or a method of privilege elevation. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |
None |
104 |
|
Looks for anomalous access to the cloud platform metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |
None |
104 |
|
Looks for commands related to system user or owner discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system owner or user discovery in order to identify currently active or primary users of a system. This may be a precursor to additional discovery, credential dumping or privilege elevation activity. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |
None |
105 |
|
A machine learning job detected activity for a username that is not normally active, which can indicate unauthorized changes, activity by unauthorized users, lateral movement, or compromised credentials. In many organizations, new usernames are not often created apart from specific types of system activities, such as creating new accounts for new employees. These user accounts quickly become active and routine. Events from rarely used usernames can point to suspicious activity. Additionally, automated Linux fleets tend to see activity from rarely used usernames only when personnel log in to make authorized or unauthorized changes, or threat actors have acquired credentials and log in for malicious purposes. Unusual usernames can also indicate pivoting, where compromised credentials are used to try and move laterally from one host to another. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |
None |
104 |
|
Identifies an unusually high number of authentication attempts. |
[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |
None |
104 |
|
Identifies network activity from unexpected system applications. This may indicate adversarial activity as these applications are often leveraged by adversaries to execute code and evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
113 |
|
Identifies unusual instances of dllhost.exe making outbound network connections. This may indicate adversarial Command and Control activity. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
107 |
|
Identifies unusual instances of rundll32.exe making outbound network connections. This may indicate adversarial Command and Control activity. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
109 |
|
A machine learning job detected an unusual network destination domain name. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from an uncommon web server name. When malware is already running, it may send requests to an uncommon DNS domain the malware uses for command-and-control communication. |
[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |
None |
104 |
|
Identifies a suspicious parent child process relationship with cmd.exe descending from an unusual process. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne], [Data Source: Microsoft Defender for Endpoint] |
8.13.0 |
313 |
|
Identifies Windows programs run from unexpected parent processes. This could indicate masquerading or other strange activity on a system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
213 |
|
Identifies processes modifying the services registry key directly, instead of through the expected Windows APIs. This could be an indication of an adversary attempting to stealthily persist through abnormal service creation or modification of an existing service. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Detects unusual Print Spooler service (spoolsv.exe) child processes. This may indicate an attempt to exploit privilege escalation vulnerabilities related to the Printing Service on Windows. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: System] |
None |
109 |
|
Identifies processes running from an Alternate Data Stream. This is uncommon for legitimate processes and sometimes done by adversaries to hide malware. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
209 |
|
Identifies unusual processes running from the WBEM path, uncommon outside WMI-related Windows processes. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame], [Data Source: System] |
None |
4 |
|
Identifies processes running with unusual extensions that are not typically valid for Windows executables. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
4 |
|
Identifies unusual process executions using MSSQL Service accounts, which can indicate the exploitation/compromise of SQL instances. Attackers may exploit exposed MSSQL instances for initial access or lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
4 |
|
Identifies rare processes that do not usually run on individual hosts, which can indicate execution of unauthorized services, malware, or persistence mechanisms. Processes are considered rare when they only run occasionally as compared with other processes running on the host. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence] |
None |
105 |
|
Identifies rare processes that do not usually run on individual hosts, which can indicate execution of unauthorized services, malware, or persistence mechanisms. Processes are considered rare when they only run occasionally as compared with other processes running on the host. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Resources: Investigation Guide] |
None |
111 |
|
Identifies network activity from unexpected system applications. This may indicate adversarial activity as these applications are often leveraged by adversaries to execute code and evade detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
108 |
|
A machine learning job has detected a suspicious Windows process. This process has been classified as suspicious in two ways. It was predicted to be suspicious by the ProblemChild supervised ML model, and it was found to be an unusual process, on a host that does not commonly manifest malicious activity. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |
[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |
None |
7 |
|
A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be an unusual child process name, for the parent process, by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |
[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |
None |
7 |
|
A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be suspicious given that its user context is unusual and does not commonly manifest malicious activity,by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |
[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |
None |
7 |
|
A machine learning job has detected a rare process writing data to an external device. Malicious actors often use benign-looking processes to mask their data exfiltration activities. The discovery of such a process that has no legitimate reason to write data to external devices can indicate exfiltration. |
[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |
None |
4 |
|
An anomaly detection job has detected a remote file transfer on an unusual directory indicating a potential lateral movement activity on the host. Many Security solutions monitor well-known directories for suspicious activities, so attackers might use less common directories to bypass monitoring. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
An anomaly detection job has detected a remote file transfer with a rare extension, which could indicate potential lateral movement activity on the host. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
A machine learning job has detected an unusually high file size shared by a remote host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Instead of multiple small transfers that can raise alarms, attackers might choose to bundle data into a single large file transfer. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
Identifies unusual child processes of Service Host (svchost.exe) that traditionally do not spawn any child processes. This may indicate a code injection or an equivalent form of exploitation. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
A machine learning job detected a user logging in from an IP address that is unusual for the user. This can be due to credentialed access via a compromised account when the user and the threat actor are in different locations. An unusual source IP address for a username could also be due to lateral movement when a compromised account is used to pivot between hosts. |
[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |
None |
104 |
|
Looks for sudo activity from an unusual user context. An unusual sudo user could be due to troubleshooting activity or it could be a sign of credentialed access via compromised accounts. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Privilege Escalation] |
None |
104 |
|
A machine learning job has detected an RDP session started at an usual time or weekday. An RDP session at an unusual time could be followed by other suspicious activities, so catching this is a good first step in detecting a larger attack. |
[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |
None |
4 |
|
This rule monitors for a sequence of 20 "id" command executions within 1 second by the same parent process. This behavior is unusual, and may be indicative of the execution of an enumeration script such as LinPEAS or LinEnum. These scripts leverage the "id" command to enumerate the privileges of all users present on the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |
None |
4 |
|
A machine learning job detected a rare and unusual URL that indicates unusual web browsing activity. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, in a strategic web compromise or watering hole attack, when a trusted website is compromised to target a particular sector or organization, targeted users may receive emails with uncommon URLs for trusted websites. These URLs can be used to download and run a payload. When malware is already running, it may send requests to uncommon URLs on trusted websites the malware uses for command-and-control communication. When rare URLs are observed being requested for a local web server by a remote source, these can be due to web scanning, enumeration or attack traffic, or they can be due to bots and web scrapers which are part of common Internet background traffic. |
[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |
None |
104 |
|
A machine learning job detected a rare and unusual user agent indicating web browsing activity by an unusual process other than a web browser. This can be due to persistence, command-and-control, or exfiltration activity. Uncommon user agents coming from remote sources to local destinations are often the result of scanners, bots, and web scrapers, which are part of common Internet background traffic. Much of this is noise, but more targeted attacks on websites using tools like Burp or SQLmap can sometimes be discovered by spotting uncommon user agents. Uncommon user agents in traffic from local sources to remote destinations can be any number of things, including harmless programs like weather monitoring or stock-trading programs. However, uncommon user agents from local sources can also be due to malware or scanning activity. |
[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |
None |
104 |
|
Identifies Windows processes that do not usually use the network but have unexpected network activity, which can indicate command-and-control, lateral movement, persistence, or data exfiltration activity. A process with unusual network activity can denote process exploitation or injection, where the process is used to run persistence mechanisms that allow a malicious actor remote access or control of the host, data exfiltration, and execution of unauthorized network applications. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |
None |
106 |
|
Identifies processes started from atypical folders in the file system, which might indicate malware execution or persistence mechanisms. In corporate Windows environments, software installation is centrally managed and it is unusual for programs to be executed from user or temporary directories. Processes executed from these locations can denote that a user downloaded software directly from the Internet or a malicious script or macro executed malware. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Tactic: Execution] |
None |
107 |
|
Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |
None |
106 |
|
A machine learning job detected an unusual remote desktop protocol (RDP) username, which can indicate account takeover or credentialed persistence using compromised accounts. RDP attacks, such as BlueKeep, also tend to use unusual usernames. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |
None |
106 |
|
A machine learning job detected an unusual Windows service, This can indicate execution of unauthorized services, malware, or persistence mechanisms. In corporate Windows environments, hosts do not generally run many rare or unique services. This job helps detect malware and persistence mechanisms that have been installed and run as a service. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence] |
None |
106 |
|
Looks for anomalous access to the cloud platform metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |
None |
106 |
|
A machine learning job detected an unusual user context switch, using the runas command or similar techniques, which can indicate account takeover or privilege escalation using compromised accounts. Privilege elevation using tools like runas are more commonly used by domain and network administrators than by regular Windows users. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Privilege Escalation] |
None |
106 |
|
A machine learning job detected activity for a username that is not normally active, which can indicate unauthorized changes, activity by unauthorized users, lateral movement, or compromised credentials. In many organizations, new usernames are not often created apart from specific types of system activities, such as creating new accounts for new employees. These user accounts quickly become active and routine. Events from rarely used usernames can point to suspicious activity. Additionally, automated Linux fleets tend to see activity from rarely used usernames only when personnel log in to make authorized or unauthorized changes, or threat actors have acquired credentials and log in for malicious purposes. Unusual usernames can also indicate pivoting, where compromised credentials are used to try and move laterally from one host to another. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |
None |
107 |
|
Identifies attempts to create new users. This is sometimes done by attackers to increase access or establish persistence on a system or domain. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies when a user is added as an owner for an Azure application. An adversary may add a user account as an owner for an Azure application in order to grant additional permissions and modify the application’s configuration using another account. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |
None |
102 |
|
Identifies when a user is added as an owner for an Azure service principal. The service principal object defines what the application can do in the specific tenant, who can access the application, and what resources the app can access. A service principal object is created when an application is given permission to access resources in a tenant. An adversary may add a user account as an owner for a service principal and use that account in order to define what an application can do in the Azure AD tenant. |
[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |
None |
102 |
|
Identifies a user being added to a privileged group in Active Directory. Privileged accounts and groups in Active Directory are those to which powerful rights, privileges, and permissions are granted that allow them to perform nearly any action in Active Directory and on domain-joined systems. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Data Source: System] |
None |
111 |
|
Identifies users being added to the admin group. This could be an indication of privilege escalation activity. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Jamf Protect] |
8.12.0 |
1 |
|
Detects when a user account has the servicePrincipalName attribute modified. Attackers can abuse write privileges over a user to configure Service Principle Names (SPNs) so that they can perform Kerberoasting. Administrators can also configure this for legitimate purposes, exposing the account to Kerberoasting. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: System] |
None |
113 |
|
This rule leverages the |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Auditd Manager] |
None |
3 |
|
This rule detects network events that may indicate the use of VNC traffic from the Internet. VNC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |
[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection], [Data Source: PAN-OS] |
None |
105 |
|
This rule detects network events that may indicate the use of VNC traffic to the Internet. VNC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |
[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection], [Data Source: PAN-OS] |
None |
105 |
|
Identifies potential credential decrypt operations by PowerShell or unsigned processes using the Veeam.Backup.Common.dll library. Attackers can use Veeam Credentials to target backups as part of destructive operations such as Ransomware attacks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
2 |
|
An adversary may attempt to get detailed information about the operating system and hardware. This rule identifies common locations used to discover virtual machine hardware by a non-root user. This technique has been used by the Pupy RAT and other malware. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |
None |
108 |
|
An adversary may attempt to get detailed information about the operating system and hardware. This rule identifies common locations used to discover virtual machine hardware by a non-root user. This technique has been used by the Pupy RAT and other malware. |
[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |
None |
105 |
|
Identifies the execution of macOS built-in commands to connect to an existing Virtual Private Network (VPN). Adversaries may use VPN connections to laterally move and control remote systems on a network. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |
None |
107 |
|
Identifies use of vssadmin.exe for shadow copy deletion or resizing on endpoints. This commonly occurs in tandem with ransomware or other destructive attacks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies the use of the Win32_ShadowCopy class and related cmdlets to achieve shadow copy deletion. This commonly occurs in tandem with ransomware or other destructive attacks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies use of wmic.exe for shadow copy deletion on endpoints. This commonly occurs in tandem with ransomware or other destructive attacks. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies processes executed via Windows Management Instrumentation (WMI) on a remote host. This could be indicative of adversary lateral movement, but could be noisy if administrators use WMI to remotely manage hosts. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
110 |
|
Adversaries may abuse the WMI diagnostic tool, wbemtest.exe, to enumerate WMI object instances or invoke methods against local or remote endpoints. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame], [Data Source: System] |
None |
4 |
|
Identifies the use of wmic.exe to run commands on remote hosts. While this can be used by administrators legitimately, attackers can abuse this built-in utility to achieve lateral movement. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Sysmon], [Data Source: Elastic Endgame], [Data Source: System] |
None |
7 |
|
Identifies the load of a remote library by the WPS Office promecefpluginhost.exe executable. This may indicate the successful exploitation of CVE-2024-7262 or CVE-2024-7263 via DLL hijack abusing the ksoqing custom protocol handler. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
1 |
|
Identifies the access on an object with WRITEDAC permissions. With the WRITEDAC permission, the user can perform a Write Discretionary Access Control List (WriteDACL) operation, which is used to modify the access control rules associated with a specific object within Active Directory. Attackers may abuse this privilege to grant themselves or other compromised accounts additional rights, ultimately compromising the target object, resulting in privilege escalation, lateral movement, and persistence. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Active Directory], [Use Case: Active Directory Monitoring], [Rule Type: BBR], [Data Source: System] |
None |
7 |
|
A POST request to a web application returned a 403 response, which indicates the web application declined to process the request because the action requested was not allowed. |
[Data Source: APM] |
None |
102 |
|
A request to a web application returned a 405 response, which indicates the web application declined to process the request because the HTTP method is not allowed for the resource. |
[Data Source: APM] |
None |
102 |
|
This is an example of how to detect an unwanted web client user agent. This search matches the user agent for sqlmap 1.3.11, which is a popular FOSS tool for testing web applications for SQL injection vulnerabilities. |
[Data Source: APM] |
None |
102 |
|
This rule identifies when a web server is spawned via Python. Attackers may use Python to spawn a web server to exfiltrate/infiltrate data or to move laterally within a network. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |
None |
1 |
|
Web Shell Detection: Script Process Child of Common Web Processes |
Identifies suspicious commands executed via a web server, which may suggest a vulnerability and remote shell access. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Initial Access], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon] |
8.13.0 |
315 |
Identifies the use of the built-in networksetup command to configure webproxy settings. This may indicate an attempt to hijack web browser traffic for credential access via traffic sniffing or redirection. |
[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |
None |
206 |
|
Identifies the deletion of WebServer access logs. This may indicate an attempt to evade detection or destroy forensic evidence on a system. |
[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
107 |
|
Identifies the registration of a Werfault Debugger. Attackers may abuse this mechanism to execute malicious payloads every time the utility is executed with the "-pr" parameter. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne], [Data Source: Sysmon] |
8.13.0 |
102 |
|
Identifies suspicious use of whoami.exe which displays user, group, and privileges information for the user who is currently logged on to the local system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Microsoft Defender for Endpoint], [Data Source: System] |
None |
113 |
|
This rule identifies the execution of commands that enumerates account or group information. Adversaries may use built-in applications to get a listing of local system or domain accounts and groups. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
5 |
|
Windows CryptoAPI Spoofing Vulnerability (CVE-2020-0601 - CurveBall) |
A spoofing vulnerability exists in the way Windows CryptoAPI (Crypt32.dll) validates Elliptic Curve Cryptography (ECC) certificates. An attacker could exploit the vulnerability by using a spoofed code-signing certificate to sign a malicious executable, making it appear the file was from a trusted, legitimate source. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Use Case: Vulnerability], [Data Source: System] |
None |
107 |
Identifies modifications to the Windows Defender registry settings to disable the service or set the service to be started manually. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint] |
None |
115 |
|
Identifies modifications to the Windows Defender configuration settings using PowerShell to add exclusions at the folder directory or process level. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies attempts to clear Windows event log stores. This is often done by attackers in an attempt to evade detection or destroy forensic evidence on a system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: System] |
None |
111 |
|
Identifies when the Windows Firewall is disabled using PowerShell cmdlets, which can help attackers evade network constraints, like internet and network lateral communication restrictions. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
210 |
|
Identifies the execution of an installer from an archive or with suspicious properties. Adversaries may abuse msiexec.exe to launch local or network accessible MSI files in an attempt to bypass application whitelisting. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
2 |
|
Identifies attempts to enumerate hosts in a network using the built-in Windows net.exe tool. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |
None |
114 |
|
Identifies the creation or modification of a medium-size registry hive file on a Server Message Block (SMB) share, which may indicate an exfiltration attempt of a previously dumped Security Account Manager (SAM) registry hive for credential extraction on an attacker-controlled system. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
109 |
|
Identifies a PowerShell process launched by either cscript.exe or wscript.exe. Observing Windows scripting processes executing a PowerShell script, may be indicative of malicious activity. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
212 |
|
Identifies use of the built-in Windows script interpreters (cscript.exe or wscript.exe) being used to execute a process via Windows Management Instrumentation (WMI). This may be indicative of malicious activity. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |
None |
110 |
|
Identifies the creation of a Windows service by an unusual client process. Services may be created with administrator privileges but are executed under SYSTEM privileges, so an adversary may also use a service to escalate privileges from administrator to SYSTEM. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: System] |
None |
111 |
|
Detects changes to the registry that indicates the install of a new Windows Subsystem for Linux distribution by name. Adversaries may enable and use WSL for Linux to avoid detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: Microsoft Defender for Endpoint], [Data Source: SentinelOne] |
8.13.0 |
108 |
|
Detects attempts to enable the Windows Subsystem for Linux using Microsoft Dism utility. Adversaries may enable and use WSL for Linux to avoid detection. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
108 |
|
Detects the execution of commands used to discover information about the system, which attackers may use after compromising a system to gain situational awareness. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: System] |
None |
8 |
|
This rule identifies the execution of commands that can be used to enumerate network connections. Adversaries may attempt to get a listing of network connections to or from a compromised system to identify targets within an environment. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |
None |
4 |
|
Identifies attempts to dump Wireless saved access keys in clear text using the Windows built-in utility Netsh. |
[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Discovery], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: System], [Data Source: Microsoft Defender for Endpoint], [Data Source: Sysmon], [Data Source: SentinelOne] |
8.13.0 |
109 |
|
Detects file creation events in the plugin directories for the Yum package manager. In Linux, Yum (Yellowdog Updater, Modified) is a command-line utility used for handling packages on (by default) Fedora-based systems, providing functions for installing, updating, upgrading, and removing software along with managing package repositories. Attackers can backdoor Yum to gain persistence by injecting malicious code into plugins that Yum runs, thereby ensuring continued unauthorized access or control each time Yum is used for package management. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |
None |
4 |
|
This rule detects the execution of the |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |
None |
2 |
|
This rule identifies Zoom meetings that are created without a passcode. Meetings without a passcode are susceptible to Zoombombing. Zoombombing is carried out by taking advantage of Zoom sessions that are not protected with a passcode. Zoombombing refers to the unwanted, disruptive intrusion, generally by Internet trolls and hackers, into a video conference call. In a typical Zoombombing incident, a teleconferencing session is hijacked by the insertion of material that is lewd, obscene, racist, or antisemitic in nature, typically resulting of the shutdown of the session. |
[Data Source: Zoom], [Use Case: Configuration Audit], [Tactic: Initial Access] |
None |
103 |
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This rule monitors the creation/alteration of the rc.local/rc.common file. The /etc/rc.local file is used to start custom applications, services, scripts or commands during start-up. The rc.local file has mostly been replaced by Systemd. However, through the "systemd-rc-local-generator", rc.local files can be converted to services that run at boot. Adversaries may alter rc.local/rc.common to execute malicious code at start-up, and gain persistence onto the system. |
[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Defend] |
None |
114 |