Detection: Linux Suspicious Privileged Container Execution

Description

The following analytic detects the execution of a Docker container with the privileged flag set, or with the pid namespace set to the host. This can indicate a container running with elevated permissions and access to the underlying system. Actors can hide containers such as this to enable persistent access.

 1
 2| tstats `security_content_summariesonly`
 3  count min(_time) as firstTime
 4        max(_time) as lastTime
 5
 6from datamodel=Endpoint.Processes where
 7
 8Processes.process="*docker *"
 9Processes.process="* run*"
10Processes.process IN ("*--privileged*", "*--pid=host*")
11
12by Processes.process Processes.vendor_product Processes.user_id
13   Processes.process_hash Processes.parent_process_name
14   Processes.parent_process_exec Processes.action Processes.dest Processes.process_current_directory
15   Processes.process_path Processes.process_integrity_level Processes.original_file_name
16   Processes.parent_process Processes.parent_process_path Processes.parent_process_guid
17   Processes.parent_process_id Processes.process_guid Processes.process_id Processes.user
18   Processes.process_name
19
20| `drop_dm_object_name(Processes)`
21
22| `security_content_ctime(firstTime)`
23
24| `security_content_ctime(lastTime)`
25
26| `linux_suspicious_privileged_container_execution_filter`

Data Source

Name Platform Sourcetype Source
Sysmon for Linux EventID 1 Linux icon Linux 'sysmon:linux' 'Syslog:Linux-Sysmon/Operational'

Macros Used

Name Value
security_content_summariesonly summariesonly=summariesonly_config allow_old_summaries=oldsummaries_config fillnull_value=fillnull_config``
linux_suspicious_privileged_container_execution_filter search *
linux_suspicious_privileged_container_execution_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1059.004 Unix Shell Execution
T1610 Deploy Container Execution
Installation
DE.AE
CIS 10

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Finding (Notable) No
Creates Intermediate Finding (Risk Event) Yes
Anomaly detections generate Intermediate Findings (Risk Events). They do not generate a Finding (Notable) directly.

Implementation

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

Legitimate system administrators may intentionally run privileged containers for maintenance, debugging, or specific infrastructure tasks. Filter based on known approved workflows and trusted administrative users.

Associated Analytic Story

Intermediate Findings

Message Entity Field Entity Type Risk Score
Suspicious Privileged Container identified on [$dest$] via [$process_name$] with the Command Line [$process$]. dest system 20

Threat Objects

Field Type
process process
process_name process_name

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Passing N/A N/A N/A
Unit Passing Dataset Syslog:Linux-Sysmon/Operational sysmon:linux
Integration ✅ Passing Dataset Syslog:Linux-Sysmon/Operational sysmon:linux

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range


Source: GitHub |

Version: 1