Name:Windows PowGoop Beacon Decoding id:4d0480d8-80c4-4f74-84fe-2ab7fb514c85 version:2 date:None author:Raven Tait, Splunk status:production type:TTP Description:Detects a DLL decoding and executing the PowGoop config.txt payload, the stage in the MuddyWater infection chain where an obfuscated PowerShell beacon is unwrapped and live C2 communication begins.
PowGoop is the primary loader used by MuddyWater (also tracked as SeedWorm, Static Kitten, and MERCURY) and has been their main initial access loader since at least 2020.
It abuses DLL side-loading against a fake GoogleUpdate.exe to execute a multi-stage decoding chain, a fully functional PowerShell backdoor disguised with a benign extension.
The config.txt contains a hardcoded C2 address and victim GUID, beacons via modified base64-encoded HTTP, and runs C2 traffic under the legitimate Google Update process to evade network detection. Data_source:
-Sysmon EventID 1
-CrowdStrike ProcessRollup2
search:| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime
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 security tools or legitimate debugging processes may decode config files similar to PowGoop. Review and whitelist trusted applications to reduce false alerts. References: -https://www.cisa.gov/uscert/sites/default/files/publications/AA22-055A_Iranian_Government-Sponsored_Actors_Conduct_Cyber_Operations.pdf 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:['Compromised Windows Host']
