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Description

The following analytic detects suspicious use of the modprobe command to unload kernel modules, which may indicate an attempt to disable critical system components or evade detection. The modprobe utility manages kernel modules, and unauthorized unloading of modules can disrupt system security features, remove logging capabilities, or conceal malicious activities. By monitoring for unusual or unauthorized modprobe operations involving module unloading, this analytic helps identify potential tampering with kernel functionality, enabling security teams to investigate and address possible threats to system integrity.

  • Type: TTP

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

  • Last Updated: 2024-09-04
  • Author: Teoderick Contreras, Splunk
  • ID: 90964d6a-4b5f-409a-85bd-95e261e03fe9

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` `linux_auditd_normalized_execve_process` 
| rename host as dest 
| where LIKE (process_exec, "%modprobe%") AND  LIKE (process_exec, "%-r %") 
| stats count min(_time) as firstTime max(_time) as lastTime by argc process_exec dest 
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `linux_auditd_unload_module_via_modprobe_filter`

Macros

The SPL above uses the following Macros:

:information_source: linux_auditd_unload_module_via_modprobe_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
  • argc
  • process_exec

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
49.0 70 70 A [$process_exec$] event occurred on host - [$dest$] to unload a kernel module via the modprobe command.

: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

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