ID | Technique | Tactic |
---|---|---|
T1548.003 | Sudo and Sudo Caching | Defense Evasion |
T1548 | Abuse Elevation Control Mechanism | Privilege Escalation |
Detection: Linux Auditd Doas Tool Execution
Description
The following analytic detects the execution of the 'doas' tool on a Linux host. This tool allows standard users to perform tasks with root privileges, similar to 'sudo'. The detection leverages data from Linux Auditd, focusing on process names and command-line executions. This activity is significant as 'doas' can be exploited by adversaries to gain elevated privileges on a compromised host. If confirmed malicious, this could lead to unauthorized administrative access, potentially compromising the entire system.
Search
1`linux_auditd` type=SYSCALL comm=doas
2| rename host as dest
3| stats count min(_time) as firstTime max(_time) as lastTime by comm exe SYSCALL UID ppid pid success dest
4| `security_content_ctime(firstTime)`
5| `security_content_ctime(lastTime)`
6| `linux_auditd_doas_tool_execution_filter`
Data Source
Name | Platform | Sourcetype | Source |
---|---|---|---|
Linux Auditd Syscall | Linux | 'linux:audit' |
'/var/log/audit/audit.log' |
Macros Used
Name | Value |
---|---|
linux_auditd | sourcetype="linux:audit" |
linux_auditd_doas_tool_execution_filter | search * |
linux_auditd_doas_tool_execution_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Risk Event | True |
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 execute this command. Please update the filter macros to remove false positives.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
A SYSCALL - [$comm$] event was executed on host - [$dest$] to execute the "doas" tool. | 49 | 70 | 70 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | /var/log/audit/audit.log |
linux:audit |
Integration | ✅ Passing | Dataset | /var/log/audit/audit.log |
linux:audit |
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: 1