Name:Possible Lateral Movement PowerShell Spawn id:cb909b3e-512b-11ec-aa31-3e22fbd008af version:17 date:None author:Mauricio Velazco, Michael Haag, Splunk status:production type:Anomaly Description:The following analytic detects the spawning of a PowerShell process as a child or grandchild of commonly abused processes like services.exe, wmiprvse.exe, svchost.exe, wsmprovhost.exe, and mmc.exe.
It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and parent process names, as well as command-line executions.
This activity is significant as it could indicates lateral movement or remote code execution attempts by adversaries.
If confirmed malicious, this behavior could allow attackers to execute code remotely, escalate privileges, or persist within the environment.
Data_source:
-Sysmon EventID 1
-CrowdStrike ProcessRollup2
search:| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where
( Processes.parent_process_name IN ( "mmc.exe", "services.exe", "wmiprvse.exe", "wsmprovhost.exe" ) OR ( Processes.parent_process_name="svchost.exe" ``` We exclude the "Schedule" service from the svchost.exe process. But since there are instances where its not hosted in a dedicated svchost process, we need to the hosting group "netsvcs" too ``` NOT Processes.parent_process IN ( "*-k netsvcs*", "*-s Schedule*", ) ) ) AND ( Processes.process_name IN ("powershell.exe", "pwsh.exe") OR ( Processes.process_name=cmd.exe Processes.process IN ( "*powershell*", "*pwsh*" ) ) ) NOT Processes.process IN ("*C:\\Windows\\CCM\\*")
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:False positives are expected from legitimate use of WMI or certain services. Apply additoinal filters as needed.
References: -https://attack.mitre.org/techniques/T1021/003/ -https://attack.mitre.org/techniques/T1021/006/ -https://attack.mitre.org/techniques/T1047/ -https://attack.mitre.org/techniques/T1053/005/ -https://attack.mitre.org/techniques/T1543/003/ drilldown_searches: name:'View the detection results for - "$dest$"' search:'%original_detection_search% | search dest = "$dest$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$dest$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' earliest_offset:'7d' latest_offset:'0' analytic_story:['Active Directory Lateral Movement', 'Malicious PowerShell', 'Hermetic Wiper', 'Data Destruction', 'Scheduled Tasks', 'CISA AA24-241A', 'Microsoft WSUS CVE-2025-59287']
