ID | Technique | Tactic |
---|---|---|
T1136.001 | Local Account | Persistence |
T1136 | Create Account | Persistence |
Detection: Linux Auditd Add User Account
Description
The following analytic detects the creation of new user accounts on Linux systems using commands like "useradd" or "adduser." It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as adversaries often create new user accounts to establish persistence on compromised hosts. If confirmed malicious, this could allow attackers to maintain access, escalate privileges, and further compromise the system, posing a severe security risk.
Search
1`linux_auditd` `linux_auditd_normalized_proctitle_process`
2| rename host as dest
3| where LIKE (process_exec, "%useradd%") OR LIKE (process_exec, "%adduser%")
4| stats count min(_time) as firstTime max(_time) as lastTime by process_exec proctitle dest
5| `security_content_ctime(firstTime)`
6| `security_content_ctime(lastTime)`
7| `linux_auditd_add_user_account_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
Linux Auditd Proctitle | Linux | 'linux:audit' |
'/var/log/audit/audit.log' |
N/A |
Macros Used
Name | Value |
---|---|
linux_auditd | sourcetype="linux:audit" |
linux_auditd_add_user_account_filter | search * |
linux_auditd_add_user_account_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 [$process_exec$] event occurred on host - [$dest$] to add a user account. | 25 | 50 | 50 |
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