Name:Windows Sensitive Registry Hive Dump Via CommandLine id:5aaff29d-0cce-405b-9ee8-5d06b49d045e version:3 date:2025-02-10 author:Michael Haag, Patrick Bareiss, Nasreddine Bencherchali, Splunk status:production type:TTP Description:The following analytic detects the use of `reg.exe` to export Windows Registry hives, which may contain sensitive credentials. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions involving `save` or `export` actions targeting the `sam`, `system`, or `security` hives. This activity is significant as it indicates potential offline credential access attacks, often executed from untrusted processes or scripts. If confirmed malicious, attackers could gain access to credential data, enabling further compromise and lateral movement within the network. Data_source:
-Sysmon EventID 1
-Windows Event Log Security 4688
-CrowdStrike ProcessRollup2
search:| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where ((`process_reg` Processes.process IN ("*save*", "*export*")) OR (`process_regedit` Processes.process IN ("*/E *", "*-E *"))) AND Processes.process IN ("*HKEY_LOCAL_MACHINE*", "*HKLM*") AND Processes.process IN ("*SAM*", "*System*", "*Security*") by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.parent_process_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_sensitive_registry_hive_dump_via_commandline_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:It is possible some agent based products will generate false positives. Filter as needed. References: -https://www.mandiant.com/resources/shining-a-light-on-darkside-ransomware-operations -https://github.com/redcanaryco/atomic-red-team/blob/master/atomics/T1003.002/T1003.002.md -https://media.defense.gov/2023/May/24/2003229517/-1/-1/0/CSA_Living_off_the_Land.PDF drilldown_searches: name:'View the detection results for - "$user$" and "$dest$"' search:'%original_detection_search% | search user = "$user$" dest = "$dest$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$user$" and "$dest$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") starthoursago=168 | 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:'$info_min_time$' latest_offset:'$info_max_time$' tags: analytic_story: - 'CISA AA22-257A' - 'CISA AA23-347A' - 'Compromised Windows Host' - 'Credential Dumping' - 'DarkSide Ransomware' - 'Data Destruction' - 'Industroyer2' - 'Volt Typhoon' - 'Windows Registry Abuse' asset_type:Endpoint mitre_attack_id: - 'T1003.002' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' security_domain:endpoint
