High Variance in RDP Session Duration
editHigh Variance in RDP Session Duration
editA 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.
Rule type: machine_learning
Rule indices: None
Severity: low
Risk score: 21
Runs every: 15m
Searches indices from: now-12h (Date Math format, see also Additional look-back time)
Maximum alerts per execution: 100
References:
Tags:
- Use Case: Lateral Movement Detection
- Rule Type: ML
- Rule Type: Machine Learning
- Tactic: Lateral Movement
Version: 3
Rule authors:
- Elastic
Rule license: Elastic License v2
Setup
editSetup
The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.
Lateral Movement Detection Setup
The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic’s Anomaly Detection feature.
Prerequisite Requirements:
- Fleet is required for Lateral Movement Detection.
- To configure Fleet Server refer to the documentation.
- Windows RDP process events collected by the Elastic Defend integration.
- To install Elastic Defend, refer to the documentation.
The following steps should be executed to install assets associated with the Lateral Movement Detection integration:
- Go to the Kibana homepage. Under Management, click Integrations.
- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
Anomaly Detection Setup
Before you can enable rules for Lateral Movement Detection, you’ll need to enable the corresponding Anomaly Detection jobs.
- Before enabling the Anomaly Detection jobs, confirm that the Pivot Transform asset is installed and actively gathering data in the destination index ml-rdp-lmd.
- Go to the Kibana homepage. Under Analytics, click Machine Learning.
- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your transformed RDP process data i.e.ml-rdp-lmd.
- If the selected Data View contains events that match the query in this configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
Framework: MITRE ATT&CKTM
-
Tactic:
- Name: Lateral Movement
- ID: TA0008
- Reference URL: https://attack.mitre.org/tactics/TA0008/
-
Technique:
- Name: Exploitation of Remote Services
- ID: T1210
- Reference URL: https://attack.mitre.org/techniques/T1210/