Linux Data Destruction Command

 Original Source: [splunk source]
Name:Linux Data Destruction Command
id:b11d3979-b2f7-411b-bb1a-bd00e642173b
version:13
date:None
author:Teoderick Contreras, Splunk
status:production
type:Anomaly
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.
Data_source:
  • -Sysmon for Linux EventID 1
search:| tstats `security_content_summariesonly`
count min(_time) as firstTime
max(_time) as lastTime

FROM datamodel=Endpoint.Processes WHERE

Processes.process_name = "rm"
Processes.process = "* --no-preserve-root*"

BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product

| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `linux_data_destruction_command_filter`


how_to_implement: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.
References:
  -https://cert.gov.ua/article/3718487
  -https://www.trustwave.com/en-us/resources/blogs/spiderlabs-blog/overview-of-the-cyber-weapons-used-in-the-ukraine-russia-war/
drilldown_searches:
 name:'View the detection results for - "$dest$" and "$user$"'
 search:'%original_detection_search% | search dest = "$dest$" user = "$user$"'
 earliest_offset:'$info_min_time$'
 latest_offset:'$info_max_time$'
 name:'View risk events for the last 7 days for - "$dest$" and "$user$"'
 search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$", "$user$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
 earliest_offset:'7d'
 latest_offset:'0'
analytic_story:['AwfulShred', 'Data Destruction']

asset_type:Endpoint

mitre_attack_id:['T1485']

product:['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud']

category:endpoint

security_domain:endpoint

tags:

tests:
 name:'True Positive Test'
 attack_data:
  data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/awfulshred/test1/sysmon_linux.log
  source: Syslog:Linux-Sysmon/Operational
  sourcetype: sysmon:linux
 test_type:'unit'
manual_test:None

Related Analytic Stories


Data Destruction

AwfulShred