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https://github.com/splunk/security_content
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Eric
82 lines
3.7 KiB
YAML
82 lines
3.7 KiB
YAML
name: Linux Auditd Shred Overwrite Command
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id: ce2bde4d-a1d4-4452-8c87-98440e5adfb3
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version: 5
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date: '2025-05-02'
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author: Teoderick Contreras, Splunk
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status: production
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type: TTP
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description: The following analytic detects the execution of the 'shred' command on
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a Linux machine, which is used to overwrite files to make them unrecoverable. It
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leverages data from Linux Auditd, focusing on process names and command-line arguments.
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This activity is significant because the 'shred' command can be used in destructive
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attacks, such as those seen in the Industroyer2 malware targeting energy facilities.
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If confirmed malicious, this activity could lead to the permanent destruction of
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critical files, severely impacting system integrity and data availability.
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data_source:
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- Linux Auditd Proctitle
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search: '`linux_auditd` proctitle IN ("*shred*") AND proctitle IN ("*-n*", "*-z*", "*-u*", "*-s*")
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| rename host as dest
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| stats count min(_time) as firstTime max(_time) as lastTime by proctitle dest
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| `security_content_ctime(firstTime)`
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|`security_content_ctime(lastTime)`
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| `linux_auditd_shred_overwrite_command_filter`'
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how_to_implement: To implement this detection, the process begins by ingesting auditd
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data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line
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executions and process details on Unix/Linux systems. These logs should be ingested
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and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833),
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which is essential for correctly parsing and categorizing the data. The next step
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involves normalizing the field names to match the field names set by the Splunk
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Common Information Model (CIM) to ensure consistency across different data sources
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and enhance the efficiency of data modeling. This approach enables effective monitoring
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and detection of linux endpoints where auditd is deployed
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known_false_positives: Administrator or network operator can use this application
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for automation purposes. Please update the filter macros to remove false positives.
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references:
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- https://www.welivesecurity.com/2022/04/12/industroyer2-industroyer-reloaded/
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- https://cert.gov.ua/article/39518
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drilldown_searches:
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- name: View the detection results for - "$dest$"
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search: '%original_detection_search% | search dest = "$dest$"'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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- name: View risk events for the last 7 days for - "$dest$"
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search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$")
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starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime
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values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories)
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as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic)
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as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)`
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| `security_content_ctime(lastTime)`'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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rba:
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message: A [$proctitle$] event occurred on host - [$dest$] to overwrite files
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using the shred utility.
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risk_objects:
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- field: dest
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type: system
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score: 81
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threat_objects: []
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tags:
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analytic_story:
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- AwfulShred
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- Linux Privilege Escalation
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- Data Destruction
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- Linux Persistence Techniques
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- Industroyer2
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- Compromised Linux Host
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asset_type: Endpoint
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mitre_attack_id:
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- T1485
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product:
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- Splunk Enterprise
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- Splunk Enterprise Security
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- Splunk Cloud
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security_domain: endpoint
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tests:
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- name: True Positive Test
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attack_data:
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- data:
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https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1485/linux_auditd_shred/auditd_proctitle_shred.log
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source: auditd
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sourcetype: auditd
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