Name:Windows Binary Execution from an Archive id:1516a16f-391e-457f-b9a3-a81dfdf218a6 version:2 date:None author:Raven Tait, Nasreddine Bencherchali, Splunk status:experimental type:Anomaly Description:Detects the execution of a binary from archive-related paths in the user's Temp directory.
It looks for binaries launched by `explorer.exe`, `winrar.exe`, or `7zFM.exe`, where the executed process path includes Temp and archive markers such as RAR, 7z, or ZIP.
This was abused by attackers to bypass Mark-of-the-Web (MOTW) such as CVE-2025-0411 or exploit certain vulnerabilities. Data_source:
-Sysmon EventID 1
-CrowdStrike ProcessRollup2
search:| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime
from datamodel=Endpoint.Processes where
Processes.parent_process_name IN ( "explorer.exe", "winrar.exe", "7zFM.exe" ) Processes.process_path="*\\AppData\\Local\\Temp\\*" Processes.process_path IN ( "*\\rar*", "*\\7z*", "*.zip*" )
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 installers, administrative packages, or automation workflows may extract and run binaries from archive files in temporary directories. Review the parent process, executed path, and user context before tuning approved activity. References: -https://redcanary.com/threat-detection-report/threats/scarlet-goldfinch/ drilldown_searches: earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View the detection results for - "$user$" and "$dest$"' search:'%original_detection_search% | search user = "$user$" dest = "$dest$"' name:'View risk events for the last 7 days for - "$user$" and "$dest$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") | 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:['Spearphishing Attachments']
