Detection: Linux Auditd Add User Account Type

Description

The following analytic detects the suspicious add user account type. This behavior is critical for a SOC to monitor because it may indicate attempts to gain unauthorized access or maintain control over a system. Such actions could be signs of malicious activity. If confirmed, this could lead to serious consequences, including a compromised system, unauthorized access to sensitive data, or even a wider breach affecting the entire network. Detecting and responding to these signs early is essential to prevent potential security incidents.

1`linux_auditd` type=ADD_USER 
2| rename hostname as dest
3| stats count min(_time) as firstTime max(_time) as lastTime by exe pid dest res UID type 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)`
6| `linux_auditd_add_user_account_type_filter`

Data Source

Name Platform Sourcetype Source Supported App
Linux Auditd Add User Linux icon Linux 'linux:audit' '/var/log/audit/audit.log' N/A

Macros Used

Name Value
linux_auditd sourcetype="linux:audit"
linux_auditd_add_user_account_type_filter search *
linux_auditd_add_user_account_type_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1136 Create Account Persistence
T1136.001 Local Account Persistence
KillChainPhase.INSTALLATION
NistCategory.DE_AE
Cis18Value.CIS_10
Indrik Spider
Scattered Spider
APT3
APT39
APT41
APT5
Dragonfly
FIN13
Fox Kitten
Kimsuky
Leafminer
Magic Hound
TeamTNT
Wizard Spider

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
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

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 use this application for automation purposes. Please update the filter macros to remove false positives.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
New [$type$] event on host - [$dest$] to add a user account type. 25 50 50
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

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: 2