Name:Windows Process With NamedPipe CommandLine id:e64399d4-94a8-11ec-a9da-acde48001122 version:10 date:None author:Teoderick Contreras, Splunk status:production type:Anomaly Description:The following analytic detects processes with command lines containing named pipes. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process command-line executions.
This behavior is significant as it is often used by adversaries, such as those behind the Olympic Destroyer malware, for inter-process communication post-injection, aiding in defense evasion and privilege escalation.
If confirmed malicious, this activity could allow attackers to maintain persistence, escalate privileges, or evade defenses, potentially leading to further compromise of the system. Data_source:
-Sysmon EventID 1
-Windows Event Log Security 4688
-CrowdStrike ProcessRollup2
search:| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime
from datamodel=Endpoint.Processes where
Processes.process = "*\\\\.\\pipe\\*" ( NOT Processes.parent_process_path IN ( "*:\\Program Files (x86)\\*", "*:\\Program Files\\*", "*:\\Windows\\System32\\*", "*:\\Windows\\SysWOW64\\*" ) OR NOT Processes.process_path IN ( "*:\\Program Files (x86)\\*", "*:\\Program Files\\*", "*:\\Windows\\System32\\*", "*:\\Windows\\SysWOW64\\*" ) )
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:Normal browser application may use this technique. Please update the filter macros to remove false positives. References: -https://blog.talosintelligence.com/2018/02/olympic-destroyer.html 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:['Windows Defense Evasion Tactics']
