Detection: Linux Auditd Data Destruction Command

Updated Date: 2024-09-04 ID: 4da5ce1a-f71b-4e71-bb73-c0a3c73f3c3c Author: Teoderick Contreras, Splunk Type: TTP Product: Splunk Enterprise Security

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	Supported App
Linux Auditd Execve	Linux	`'linux:audit'`	`'/var/log/audit/audit.log'`	N/A

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

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic
T1485	Data Destruction	Impact

KillChainPhase.ACTIONS_ON_OBJECTIVES

NistCategory.DE_CM

Cis18Value.CIS_10

APT38

Gamaredon Group

LAPSUS$

Lazarus Group

Sandworm Team

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

This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

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

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: 1