Detection rules › Splunk

Linux Docker Shell Execution

Status
production
Severity
low
Group by
IntegrityLevel, command_line, computer_name, event_action, original_file_name, parent_command_line, parent_process_guid, parent_process_id, parent_process_name, process_guid, process_hash, process_id, process_name, user, user_id, vendor_product
Author
Gowthamaraj Rajendran, Splunk, Emil Elsetrønning
Source
github.com/splunk/security_content

This detection identifies shell execution activity associated with Docker containers on Linux systems. Specifically, it monitors for interactive or non-interactive shell processes (e.g., /bin/bash, /bin/sh, /bin/zsh) launched via Docker commands such as docker exec, or through container entrypoint overrides. Shell execution inside a container may indicate administrative troubleshooting activity. However, it can also represent post-exploitation behavior, where an attacker gains access to a container and spawns a shell to execute arbitrary commands, establish persistence, or pivot to the host.

MITRE ATT&CK coverage

Rule body splunk

name: Linux Docker Shell Execution
id: 03b2b286-fa86-4ec9-b1a1-ec19d314bdf7
version: 4
creation_date: '2026-03-10'
modification_date: '2026-05-13'
author: Gowthamaraj Rajendran, Splunk, Emil Elsetrønning
status: production
type: Anomaly
description: |
    This detection identifies shell execution activity associated with Docker containers on Linux systems.
    Specifically, it monitors for interactive or non-interactive shell processes (e.g., `/bin/bash`, `/bin/sh`, `/bin/zsh`) launched via Docker commands such as `docker exec`,  or through container entrypoint overrides.
    Shell execution inside a container may indicate administrative troubleshooting activity.
    However, it can also represent post-exploitation behavior, where an attacker gains access to a container and spawns a shell to execute arbitrary commands, establish persistence, or pivot to the host.
data_source:
    - Sysmon for Linux EventID 1
search: |-
    | tstats `security_content_summariesonly`
      count min(_time) as firstTime
            max(_time) as lastTime
    from datamodel=Endpoint.Processes where
    Processes.process_name=docker*
    Processes.process="* exec *"
    Processes.process IN (
      "* /bin/bash *",
      "* /bin/dash *",
      "* /bin/sh *",
      "* /bin/zsh *",
      "* bash *",
      "* bash",
      "* dash *",
      "* dash",
      "* sh *",
      "* sh",
      "* zsh *",
      "* zsh"
    )
    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)`
    | `linux_docker_shell_execution_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: |
    False positives are present based on automated tooling or system administrative usage. Filter as needed.
references:
    - https://docs.docker.com/reference/cli/docker/container/exec/
    - https://gtfobins.github.io/gtfobins/docker/
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"
intermediate_findings:
    entities:
        - field: dest
          type: system
          score: 20
          message: $user$ on endpoint $dest$ spawned a shell in a docker container via the commandline $process$
        - field: user
          type: user
          score: 20
          message: $user$ on endpoint $dest$ spawned a shell in a docker container via the commandline $process$
threat_objects:
    - field: process
      type: process
analytic_story:
    - Linux Privilege Escalation
    - Linux Living Off The Land
asset_type: Endpoint
mitre_attack_id:
    - T1059.013
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/T1548/docker/sysmon_linux.log
          source: Syslog:Linux-Sysmon/Operational
          sourcetype: sysmon:linux
      test_type: unit

Stages and Predicates

Stage 1: tstats

| tstats `security_content_summariesonly`
  count min(_time) as firstTime
        max(_time) as lastTime
from datamodel=Endpoint.Processes where
Processes.process_name=docker*
Processes.process="* exec *"
Processes.process IN (
  "* /bin/bash *",
  "* /bin/dash *",
  "* /bin/sh *",
  "* /bin/zsh *",
  "* bash *",
  "* bash",
  "* dash *",
  "* dash",
  "* sh *",
  "* sh",
  "* zsh *",
  "* zsh"
)
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

Stage 2: search

| `drop_dm_object_name(Processes)`

Stage 3: search

| `security_content_ctime(firstTime)`

Stage 4: search

| `security_content_ctime(lastTime)`

Stage 5: search

| `linux_docker_shell_execution_filter`

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
Processes.processeq
  • "* exec *"
Processes.processin
  • "* /bin/bash *"
  • "* /bin/dash *"
  • "* /bin/sh *"
  • "* /bin/zsh *"
  • "* bash *"
  • "* bash"
  • "* dash *"
  • "* dash"
  • "* sh *"
  • "* sh"
  • "* zsh *"
  • "* zsh"
Processes.process_nameeq
  • "docker*"