mirror of
https://github.com/splunk/security_content
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Bhavin Patel
87 lines
3.5 KiB
YAML
87 lines
3.5 KiB
YAML
name: Windows AutoIt3 Execution
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id: 0ecb40d9-492b-4a57-9f87-515dd742794c
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version: 2
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date: '2024-05-28'
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author: Michael Haag, Splunk
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status: production
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type: TTP
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data_source:
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- Sysmon EventID 1
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description: The following analytic detects the execution of AutoIt3, a scripting
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language often used for automating Windows GUI tasks and general scripting. It identifies
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instances where AutoIt3 or its variants are executed by searching for process names
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or original file names matching 'autoit3.exe'. This activity is significant because
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attackers frequently use AutoIt3 to automate malicious actions, such as executing
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malware. If confirmed malicious, this activity could lead to unauthorized code execution,
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system compromise, or further propagation of malware within the environment.
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search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
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as lastTime from datamodel=Endpoint.Processes where Processes.process_name IN ("autoit3.exe",
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"autoit*.exe") OR Processes.original_file_name IN ("autoit3.exe", "autoit*.exe")
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by Processes.dest Processes.user Processes.parent_process_name Processes.process_name
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Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id
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| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`
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| `windows_autoit3_execution_filter`'
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how_to_implement: The detection is based on data that originates from Endpoint Detection
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and Response (EDR) agents. These agents are designed to provide security-related
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telemetry from the endpoints where the agent is installed. To implement this search,
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you must ingest logs that contain the process GUID, process name, and parent process.
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Additionally, you must ingest complete command-line executions. These logs must
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be processed using the appropriate Splunk Technology Add-ons that are specific to
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the EDR product. The logs must also be mapped to the `Processes` node of the `Endpoint`
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data model. Use the Splunk Common Information Model (CIM) to normalize the field
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names and speed up the data modeling process.
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known_false_positives: False positives may be present if the application is legitimately
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used, filter by user or endpoint as needed.
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references:
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- https://github.com/PaloAltoNetworks/Unit42-timely-threat-intel/blob/main/2023-10-25-IOCs-from-DarkGate-activity.txt
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tags:
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analytic_story:
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- DarkGate Malware
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asset_type: Endpoint
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atomic_guid: []
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confidence: 100
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impact: 50
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message: Execution of AutoIt3 detected. The source process is $parent_process_name$
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and the destination process is $process_name$ on $dest$ by
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mitre_attack_id:
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- T1059
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observable:
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- name: parent_process_name
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type: Process
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role:
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- Parent Process
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- name: process_name
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type: Process
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role:
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- Child Process
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- name: dest
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type: Hostname
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role:
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- Victim
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- name: user
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type: User
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role:
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- Other
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product:
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- Splunk Enterprise
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- Splunk Enterprise Security
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- Splunk Cloud
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risk_score: 50
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required_fields:
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- Processes.dest
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- Processes.user
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- Processes.parent_process_name
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- Processes.process_name
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- Processes.original_file_name
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- Processes.process
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- Processes.process_id
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- Processes.parent_process_id
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security_domain: endpoint
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tests:
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- name: True Positive Test
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attack_data:
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- data:
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https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1059/autoit/sysmon.log
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source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
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sourcetype: xmlwineventlog
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