ID | Technique | Tactic |
---|---|---|
T1485 | Data Destruction | Impact |
Detection: Linux Auditd Data Destruction Command
Description
The following analytic detects the execution of a Unix shell command designed to wipe root directories on a Linux host. It leverages data from Linux Auditd, focusing on the 'rm' command with force recursive deletion and the '--no-preserve-root' option. This activity is significant as it indicates potential data destruction attempts, often associated with malware like Awfulshred. If confirmed malicious, this behavior could lead to severe data loss, system instability, and compromised integrity of the affected Linux host. Immediate investigation and response are crucial to mitigate potential damage.
Search
1`linux_auditd` `linux_auditd_normalized_execve_process`
2| rename host as dest
3| where LIKE (process_exec, "%rm %") AND LIKE (process_exec, "% -rf %") AND LIKE (process_exec, "%--no-preserve-root%")
4| stats count min(_time) as firstTime max(_time) as lastTime by argc process_exec dest
5| `security_content_ctime(firstTime)`
6| `security_content_ctime(lastTime)`
7| `linux_auditd_data_destruction_command_filter`
Data Source
Name | Platform | Sourcetype | Source |
---|---|---|---|
Linux Auditd Execve | Linux | 'linux:audit' |
'/var/log/audit/audit.log' |
Macros Used
Name | Value |
---|---|
linux_auditd | sourcetype="linux:audit" |
linux_auditd_data_destruction_command_filter | search * |
linux_auditd_data_destruction_command_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 Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
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
unknown
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
A [$process_exec$] event occurred on host - [$dest$] to destroy data. | 90 | 100 | 90 |
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