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splunk_escuAnomaly
Windows Process With NamedPipe CommandLine
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.
Detection Query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = "*\\\\.\\pipe\\*" NOT Processes.process_path IN ("C:\\Program Files\\*", "C:\\Program Files (x86)\\*") by Processes.action Processes.dest Processes.original_file_name Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path Processes.process Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_process_with_namedpipe_commandline_filter`Author
Teoderick Contreras, Splunk
Created
2026-03-10
Data Sources
Sysmon EventID 1Windows Event Log Security 4688CrowdStrike ProcessRollup2
Tags
Windows Defense Evasion Tactics
Raw Content
name: Windows Process With NamedPipe CommandLine
id: e64399d4-94a8-11ec-a9da-acde48001122
version: 7
date: '2026-03-10'
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.process_path IN ("C:\\Program Files\\*", "C:\\Program Files (x86)\\*") by Processes.action Processes.dest Processes.original_file_name Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path Processes.process Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_process_with_namedpipe_commandline_filter`'
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 ("$dest$") starthoursago=168 | 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: $info_min_time$
latest_offset: $info_max_time$
rba:
message: Process with named pipe in $process$ on $dest$
risk_objects:
- field: dest
type: system
score: 20
threat_objects: []
tags:
analytic_story:
- Windows Defense Evasion Tactics
asset_type: Endpoint
mitre_attack_id:
- T1055
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
security_domain: endpoint
tests:
- name: True Positive Test
attack_data:
- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/olympic_destroyer/sysmon.log
source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
sourcetype: XmlWinEventLog