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The following analytic is designed to identify possible lateral movement attacks that involve the spawning of a PowerShell process as a child or grandchild process of commonly abused processes. These processes include services.exe, wmiprsve.exe, svchost.exe, wsmprovhost.exe, and mmc.exe.
Such behavior is indicative of legitimate Windows features such as the Service Control Manager, Windows Management Instrumentation, Task Scheduler, Windows Remote Management, and the DCOM protocol being abused to start a process on a remote endpoint. This behavior is often seen during lateral movement techniques where adversaries or red teams abuse these services for lateral movement and remote code execution.
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
Last Updated: 2023-04-14
Author: Mauricio Velazco, Splunk
||Distributed Component Object Model
||Windows Remote Management
||Windows Management Instrumentation
||Execution, Persistence, Privilege Escalation
||Persistence, Privilege Escalation
Kill Chain Phase
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.parent_process_name=wmiprvse.exe OR Processes.parent_process_name=services.exe OR Processes.parent_process_name=svchost.exe OR Processes.parent_process_name=wsmprovhost.exe OR Processes.parent_process_name=mmc.exe) (Processes.process_name=powershell.exe OR (Processes.process_name=cmd.exe AND Processes.process=*powershell.exe*) OR Processes.process_name=pwsh.exe OR (Processes.process_name=cmd.exe AND Processes.process=*pwsh.exe*)) by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id
The SPL above uses the following Macros:
possible_lateral_movement_powershell_spawn_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the
Processes node of the
Endpoint data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.
Known False Positives
Legitimate applications may spawn PowerShell as a child process of the the identified processes. Filter as needed.
Associated Analytic Story
||A PowerShell process was spawned as a child process of typically abused processes on $dest$
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
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Alternatively you can replay a dataset into a Splunk Attack Range
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