Linux Auditd Service Restarted
Description
The following analytic detects the restarting or re-enabling of services on Linux systems using the systemctl
or service
commands. It leverages data from Linux Auditd, focusing on process and command-line execution logs. This activity is significant as adversaries may use it to maintain persistence or execute unauthorized actions. If confirmed malicious, this behavior could lead to repeated execution of malicious payloads, unauthorized access, or data destruction. Security analysts should investigate these events to mitigate risks and prevent further compromise.
- Type: Anomaly
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2024-09-04
- Author: Teoderick Contreras, Splunk
- ID: 8eb3e858-18d3-44a4-a514-52cfa39f154a
Annotations
ATT&CK
Kill Chain Phase
- Installation
- Exploitation
NIST
- DE.AE
CIS20
- CIS 10
CVE
Search
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`linux_auditd` `linux_auditd_normalized_proctitle_process`
| rename host as dest
| where (LIKE(process_exec, "%systemctl %") OR LIKE(process_exec, "%service %") ) AND(LIKE(process_exec, "%restart%") OR LIKE(process_exec, "%reenable%") OR LIKE(process_exec, "%reload%"))
| stats count min(_time) as firstTime max(_time) as lastTime by process_exec proctitle normalized_proctitle_delimiter dest
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `linux_auditd_service_restarted_filter`
Macros
The SPL above uses the following Macros:
linux_auditd_service_restarted_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
- proctitle
How To Implement
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 commandline for automation purposes. Please update the filter macros to remove false positives.
Associated Analytic Story
- AwfulShred
- Scheduled Tasks
- Linux Privilege Escalation
- Data Destruction
- Linux Persistence Techniques
- Linux Living Off The Land
- Gomir
- Compromised Linux Host
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | A [$process_exec$] event occurred on host - [$dest$] to restart or re-enable a service. |
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: 1