Detection: Linux Auditd At Application Execution

Description

The following analytic detects the execution of the "At" application in Linux, which can be used by attackers to create persistence entries on a compromised host. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and parent process names associated with "at" or "atd". This activity is significant because the "At" application can be exploited to maintain unauthorized access or deliver additional malicious payloads. If confirmed malicious, this behavior could lead to data theft, ransomware attacks, or other severe consequences. Immediate investigation is required to determine the legitimacy of the execution and mitigate potential risks.

Search

 1`linux_auditd` type=SYSCALL comm IN ("at", "atd") OR exe IN ("/usr/bin/at","/usr/bin/atd") AND NOT (uid IN ("daemon"))
 2  
 3| rename host as dest
 4  
 5| stats count min(_time) as firstTime max(_time) as lastTime
 6    BY comm exe syscall
 7       uid ppid pid
 8       dest
 9  
10| `security_content_ctime(firstTime)`
11  
12| `security_content_ctime(lastTime)`
13  
14| `linux_auditd_at_application_execution_filter`

Data Source

Name	Platform	Sourcetype	Source
Linux Auditd Syscall	Linux	'auditd'	'auditd'

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 application for automation purposes. Please update the filter macros to remove false positives.

Associated Analytic Story

• Compromised Linux Host

• Scheduled Tasks

• Linux Persistence Techniques

• Linux Privilege Escalation

• Linux Living Off The Land

Intermediate Findings

References

• https://www.linkedin.com/pulse/getting-attacker-ip-address-from-malicious-linux-job-craig-rowland/

• https://attack.mitre.org/techniques/T1053/001/

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: 10