:warning: THIS IS A EXPERIMENTAL DETECTION

This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.

Try in Splunk Security Cloud

Description

This search detects the heap-based buffer overflow of sudoedit

  • Type: TTP

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

  • Last Updated: 2021-01-29
  • Author: Shannon Davis, Splunk
  • ID: 10f2bae0-bbe6-4984-808c-37dc1c67980d

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1068 Exploitation for Privilege Escalation Privilege Escalation
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE
ID Summary CVSS
CVE-2021-3156 Sudo before 1.9.5p2 contains an off-by-one error that can result in a heap-based buffer overflow, which allows privilege escalation to root via "sudoedit -s" and a command-line argument that ends with a single backslash character. 7.2 


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`linux_hosts` TERM(sudoedit) TERM(segfault) 
| stats count min(_time) as firstTime max(_time) as lastTime by host 
| where count > 5 
| `detect_baron_samedit_cve_2021_3156_segfault_filter`

Macros

The SPL above uses the following Macros:

:information_source: detect_baron_samedit_cve-2021-3156_segfault_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
  • host

How To Implement

Splunk Universal Forwarder running on Linux systems (tested on Centos and Ubuntu), where segfaults are being logged. This also captures instances where the exploit has been compiled into a binary. The detection looks for greater than 5 instances of sudoedit combined with segfault over your search time period on a single host

Known False Positives

If sudoedit is throwing segfaults for other reasons this will pick those up too.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 tbd

: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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