Detection: Suspicious Linux Discovery Commands

Description

The following analytic detects the execution of suspicious bash commands commonly used in scripts like AutoSUID, LinEnum, and LinPeas for system discovery on a Linux host. It leverages Endpoint Detection and Response (EDR) data, specifically looking for a high number of distinct commands executed within a short time frame. This activity is significant as it often precedes privilege escalation or other malicious actions. If confirmed malicious, an attacker could gain detailed system information, identify vulnerabilities, and potentially escalate privileges, posing a severe threat to the environment.

Search

 1
 2| tstats `security_content_summariesonly` count values(Processes.process) values(Processes.process_name) values(Processes.parent_process_name) dc(Processes.process) as distinct_commands dc(Processes.process_name) as distinct_process_names min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where [
 3|inputlookup linux_tool_discovery_process.csv 
 4| rename process as Processes.process 
 5|table Processes.process] by _time span=5m Processes.user Processes.dest 
 6| `drop_dm_object_name(Processes)` 
 7| `security_content_ctime(firstTime)` 
 8| `security_content_ctime(lastTime)`
 9| where distinct_commands > 40 AND distinct_process_names > 3
10| `suspicious_linux_discovery_commands_filter`

Data Source

Macros Used

Annotations

Default Configuration

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

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

Unless an administrator is using these commands to troubleshoot or audit a system, the execution of these commands should be monitored.

Associated Analytic Story

• Linux Post-Exploitation

Risk Based Analytics (RBA)

References

• https://attack.mitre.org/matrices/enterprise/linux/

• https://attack.mitre.org/techniques/T1059/004/

• https://github.com/IvanGlinkin/AutoSUID

• https://github.com/carlospolop/PEASS-ng/tree/master/linPEAS

• https://github.com/rebootuser/LinEnum

Detection Testing

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: 2