Detection rules › Splunk

Windows Anonymous Pipe Activity

Status
production
Group by
PipeName, dest, event_type, process_guid, process_id, process_name, signature_id
Author
Teoderick Contreras, Splunk
Source
github.com/splunk/security_content

The following analytic detects the creation or connection of anonymous pipes for inter-process communication (IPC) within a Windows environment. Anonymous pipes are commonly used by legitimate system processes, services, and applications to transfer data between related processes. However, adversaries frequently abuse anonymous pipes to facilitate stealthy process injection, command-and-control (C2) communication, credential theft, or privilege escalation. This detection monitors for unusual anonymous pipe activity, particularly involving non-system processes, unsigned executables, or unexpected parent-child process relationships. While legitimate use cases exist—such as Windows services, software installers, or security tools—unusual or high-frequency anonymous pipe activity should be investigated for potential malware, persistence mechanisms, or lateral movement techniques.

MITRE ATT&CK coverage

TacticTechniques
ExecutionT1559 Inter-Process Communication

Event coverage

Rule body splunk

name: Windows Anonymous Pipe Activity
id: ee301e1e-cd81-4011-a911-e5f049b9e3d5
version: 7
creation_date: '2025-02-13'
modification_date: '2026-05-13'
author: Teoderick Contreras, Splunk
status: production
type: Hunting
description: "The following analytic detects the creation or connection of anonymous pipes for inter-process communication (IPC) within a Windows environment. Anonymous pipes are commonly used by legitimate system processes, services, and applications to transfer data between related processes. However, adversaries frequently abuse anonymous pipes to facilitate stealthy process injection, command-and-control (C2) communication, credential theft, or privilege escalation. This detection monitors for unusual anonymous pipe activity, particularly involving non-system processes, unsigned executables, or unexpected parent-child process relationships. While legitimate use cases exist—such as Windows services, software installers, or security tools—unusual or high-frequency anonymous pipe activity should be investigated for potential malware, persistence mechanisms, or lateral movement techniques."
data_source:
    - Sysmon EventID 17
    - Sysmon EventID 18
search: '`sysmon` EventCode IN (17,18) EventType IN ( "CreatePipe", "ConnectPipe") PipeName="*Anonymous Pipe*" NOT( Image IN ("C:\\Program Files*", "C:\\Windows\\system32\\*","C:\\Windows\\syswow64\\*")) | stats  min(_time) as firstTime max(_time) as lastTime count by dest EventCode PipeName ProcessGuid ProcessId Image EventType | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_anonymous_pipe_activity_filter`'
how_to_implement: To successfully implement this search, you need to be ingesting logs with the process name and pipename from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. .
known_false_positives: Automation tool might use anonymous pipe for task orchestration or process communication.
references:
    - https://www.trendmicro.com/en_nl/research/24/k/earth-estries.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:
    - Salt Typhoon
    - China-Nexus Threat Activity
    - SnappyBee
    - Interlock Rat
    - Castle RAT
asset_type: Endpoint
mitre_attack_id:
    - T1559
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: endpoint
security_domain: endpoint
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1559/anonymous_pipe/anonymouspipe.log
          source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
          sourcetype: XmlWinEventLog
      test_type: unit

Stages and Predicates

Stage 1: search

`sysmon` EventCode IN (17,18) EventType IN ( "CreatePipe", "ConnectPipe") PipeName="*Anonymous Pipe*" NOT( Image IN ("C:\\Program Files*", "C:\\Windows\\system32\\*","C:\\Windows\\syswow64\\*"))

Stage 2: stats

| stats  min(_time) as firstTime max(_time) as lastTime count by dest EventCode PipeName ProcessGuid ProcessId Image EventType

Stage 3: search

| `security_content_ctime(firstTime)`

Stage 4: search

| `security_content_ctime(lastTime)`

Stage 5: search

| `windows_anonymous_pipe_activity_filter`

Exclusions

Top-level NOT(...) conjuncts: predicates this rule actively suppresses.

FieldKindExcluded values
Imagein"C:\\Program Files*", "C:\\Windows\\system32\\*", "C:\\Windows\\syswow64\\*"

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

FieldKindValues
EventCodein
  • 17 corpus 4 (splunk 4)
  • 18 corpus 6 (splunk 4, chronicle 1, kusto 1)
EventTypein
  • "ConnectPipe"
  • "CreatePipe"
PipeNameeq
  • "*Anonymous Pipe*"