Name:Windows CAB File on Disk id:622f08d0-69ef-42c2-8139-66088bc25acd version:12 date:None author:Michael Haag, Nasreddine Bencherchali, Splunk status:production type:Anomaly Description:The following analytic detects .cab files being written to disk.
It leverages data from Endpoint Detection and Response (EDR) agents, focusing on events where the file name is '*.cab' and the action is 'write'.
This activity can be significant as .cab files can be used to deliver malicious payloads, including embedded .url files that execute harmful code.
If confirmed malicious, this behavior could lead to unauthorized code execution and potential system compromise.
Analysts should review the file path and associated artifacts for further investigation. Data_source:
-Sysmon EventID 11
search:| tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime
FROM datamodel=Endpoint.Filesystem WHERE
Filesystem.action IN ("created", "modified") Filesystem.file_name="*.cab" NOT Filesystem.file_path IN ( "*\\AppData\\Local\\Microsoft\\*", "*\\Windows Kits\\10\\ADK\\Installers\\*", "C:\\Program Files (x86)\\*", "C:\\Program Files\\*", "C:\\ProgramData\\Microsoft\\*", "C:\\ProgramData\\Package Cache\\*", "C:\\Windows\\appcompat\\*", "C:\\Windows\\Logs\\CBS\\*", "C:\\Windows\\servicing\\*", "C:\\Windows\\SoftwareDistribution\\*", "C:\\Windows\\System32\\*", "C:\\Windows\\SystemApps\\*", "C:\\Windows\\SysWOW64\\*", "C:\\Windows\\WinSxS\\*", )
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:Some false positives are expected from user controlled folders. References: -https://github.com/PaloAltoNetworks/Unit42-timely-threat-intel/blob/main/2023-10-25-IOCs-from-DarkGate-activity.txt drilldown_searches: name:'View the detection results for - "$dest$"' search:'%original_detection_search% | search dest = "$dest$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$dest$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$") | 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:['DarkGate Malware', 'APT37 Rustonotto and FadeStealer']
