Detection: Linux Auditd Service Restarted

Description

The following analytic detects the restarting or re-enabling of services on Linux systems using the systemctl or service commands. It leverages data from Linux Auditd, focusing on process and command-line execution logs. This activity is significant as adversaries may use it to maintain persistence or execute unauthorized actions. If confirmed malicious, this behavior could lead to repeated execution of malicious payloads, unauthorized access, or data destruction. Security analysts should investigate these events to mitigate risks and prevent further compromise.

Search

1`linux_auditd` `linux_auditd_normalized_proctitle_process` 
2| rename host as dest 
3| where (LIKE(process_exec, "%systemctl %") OR LIKE(process_exec, "%service %") ) AND(LIKE(process_exec, "%restart%") OR LIKE(process_exec, "%reenable%") OR LIKE(process_exec, "%reload%")) 
4| stats count min(_time) as firstTime max(_time) as lastTime by process_exec proctitle normalized_proctitle_delimiter dest 
5| `security_content_ctime(firstTime)`
6| `security_content_ctime(lastTime)`
7| `linux_auditd_service_restarted_filter`

Data Source

Name	Platform	Sourcetype	Source
Linux Auditd Proctitle	Linux	'linux:audit'	'/var/log/audit/audit.log'

Macros Used

Annotations

Default Configuration

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

Implementation

To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed

Known False Positives

Administrator or network operator can use this commandline for automation purposes. Please update the filter macros to remove false positives.

Associated Analytic Story

• AwfulShred

• Compromised Linux Host

• Data Destruction

• Gomir

• Linux Living Off The Land

• Linux Persistence Techniques

• Linux Privilege Escalation

• Scheduled Tasks

Risk Based Analytics (RBA)

References

• https://attack.mitre.org/techniques/T1543/003/

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