Name:Windows AutoIt3 Execution id:0ecb40d9-492b-4a57-9f87-515dd742794c version:7 date:2024-11-13 author:Michael Haag, Splunk status:production type:TTP Description:The following analytic detects the execution of AutoIt3, a scripting language often used for automating Windows GUI tasks and general scripting. It identifies instances where AutoIt3 or its variants are executed by searching for process names or original file names matching 'autoit3.exe'. This activity is significant because attackers frequently use AutoIt3 to automate malicious actions, such as executing malware. If confirmed malicious, this activity could lead to unauthorized code execution, system compromise, or further propagation of malware within the environment. 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 Processes.process_name IN ("autoit3.exe", "autoit*.exe") OR Processes.original_file_name IN ("autoit3.exe", "autoit*.exe") by Processes.action Processes.dest Processes.original_file_name Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path Processes.process Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_autoit3_execution_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:False positives may be present if the application is legitimately used, filter by user or endpoint as needed. 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 - "$dest$" and "$user$"' search:'%original_detection_search% | search dest = "$dest$" user = "$user$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$dest$" and "$user$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$", "$user$") 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: - 'Crypto Stealer' - 'Handala Wiper' - 'DarkGate Malware' asset_type:Endpoint atomic_guid: mitre_attack_id: - 'T1059' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' security_domain:endpoint
