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Description

The following analytic detects suspicious use of the rmmod utility for kernel module removal, which may indicate an attacker attempt to unload critical or security-related kernel modules. The rmmod command is used to remove modules from the Linux kernel, and unauthorized use can be a tactic to disable security features, conceal malicious activities, or disrupt system operations. By monitoring for unusual or unauthorized rmmod activity, this analytic helps identify potential tampering with kernel modules, enabling security teams to take proactive measures to protect system integrity and security.

  • Type: TTP

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2024-09-04
  • Author: Teoderick Contreras, Splunk
  • ID: 31810b7a-0abe-42be-a210-0dec8106afee

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1547.006 Kernel Modules and Extensions Persistence, Privilege Escalation
T1547 Boot or Logon Autostart Execution Persistence, Privilege Escalation
Kill Chain Phase
  • Installation
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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`linux_auditd` type=SYSCALL comm=rmmod 
| rename host as dest  
| stats count min(_time) as firstTime max(_time) as lastTime by comm exe  SYSCALL UID ppid pid success dest 
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `linux_auditd_kernel_module_using_rmmod_utility_filter`

Macros

The SPL above uses the following Macros:

:information_source: linux_auditd_kernel_module_using_rmmod_utility_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • comm
  • exe
  • SYSCALL
  • UID
  • ppid
  • pid

How To Implement

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

RBA

Risk Score Impact Confidence Message
72.0 90 80 A SYSCALL - [$comm$] event was executed on host - [$dest$] to remove a Linux kernel module using the rmmod utility.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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 | version: 1