Detect Baron Samedit CVE-2021-3156 via OSQuery
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.
Description
The following analytic detects the execution of the "sudoedit -s *" command, which is associated with the Baron Samedit CVE-2021-3156 heap-based buffer overflow vulnerability. This detection leverages the osquery_process
data source to identify instances where this specific command is run. This activity is significant because it indicates an attempt to exploit a known vulnerability that allows privilege escalation. If confirmed malicious, an attacker could gain full control of the system, execute arbitrary code, or access sensitive data, leading to potential data breaches and system disruptions.
- Type: TTP
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2024-05-13
- Author: Shannon Davis, Splunk
- ID: 1de31d5d-8fa6-4ee0-af89-17069134118a
Annotations
Kill Chain Phase
- Exploitation
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
1
2
3
`osquery_process`
| search "columns.cmdline"="sudoedit -s \\*"
| `detect_baron_samedit_cve_2021_3156_via_osquery_filter`
Macros
The SPL above uses the following Macros:
detect_baron_samedit_cve-2021-3156_via_osquery_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
- columns.cmdline
How To Implement
OSQuery installed and configured to pick up process events (info at https://osquery.io) as well as using the Splunk OSQuery Add-on https://splunkbase.splunk.com/app/4402. The vulnerability is exposed when a non privledged user tries passing in a single \ character at the end of the command while using the shell and edit flags.
Known False Positives
unknown
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | tbd |
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: 2