Detection: Linux 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 Endpoint Detection and Response (EDR) agents, focusing on the 'rm' command with 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.

 1
 2| tstats `security_content_summariesonly`
 3  count min(_time) as firstTime
 4        max(_time) as lastTime
 5
 6FROM datamodel=Endpoint.Processes WHERE
 7
 8Processes.process_name = "rm"
 9Processes.process = "* --no-preserve-root*"
10
11BY Processes.action Processes.dest Processes.original_file_name
12   Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
13   Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
14   Processes.process Processes.process_exec Processes.process_guid
15   Processes.process_hash Processes.process_id Processes.process_integrity_level
16   Processes.process_name Processes.process_path Processes.user
17   Processes.user_id Processes.vendor_product
18
19
20| `drop_dm_object_name(Processes)`
21
22| `security_content_ctime(firstTime)`
23
24| `linux_data_destruction_command_filter`

Data Source

Name Platform Sourcetype Source
Sysmon for Linux EventID 1 Linux icon Linux 'sysmon:linux' 'Syslog:Linux-Sysmon/Operational'

Macros Used

Name Value
security_content_summariesonly summariesonly=summariesonly_config allow_old_summaries=oldsummaries_config fillnull_value=fillnull_config``
linux_data_destruction_command_filter search *
linux_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
Actions on Objectives
DE.AE
CIS 10

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 Finding (Notable) No
Creates Intermediate Finding (Risk Event) Yes
Anomaly detections generate Intermediate Findings (Risk Events). They do not generate a Finding (Notable) directly.

Implementation

The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Processes node of the Endpoint data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.

Known False Positives

No false positives have been identified at this time.

Associated Analytic Story

Intermediate Findings

Message Entity Field Entity Type Risk Score
The process [$process_name$] was executed with the command [$process$] that allows for the removal of files from the root directory on [$dest$]. dest system 50

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Passing N/A N/A N/A
Unit Passing Dataset Syslog:Linux-Sysmon/Operational sysmon:linux
Integration ✅ Passing Dataset Syslog:Linux-Sysmon/Operational sysmon:linux

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: 13