mirror of
https://github.com/splunk/security_content
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Bhavin Patel
82 lines
3.3 KiB
YAML
82 lines
3.3 KiB
YAML
name: Winword Spawning Windows Script Host
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id: 637e1b5c-9be1-11eb-9c32-acde48001122
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version: 2
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date: '2024-05-16'
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author: Michael Haag, Splunk
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status: production
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type: TTP
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description: The following analytic identifies instances where Microsoft Winword.exe
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spawns Windows Script Host processes (cscript.exe or wscript.exe). This behavior
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is detected using Endpoint Detection and Response (EDR) telemetry, focusing on process
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creation events where the parent process is Winword.exe. This activity is significant
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because it is uncommon and often associated with spearphishing attacks, where malicious
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scripts are executed via document macros. If confirmed malicious, this could lead
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to code execution, allowing attackers to gain initial access, execute further payloads,
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or establish persistence within the environment.
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data_source:
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- Sysmon EventID 1
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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.parent_process_name="winword.exe"
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Processes.process_name IN ("cscript.exe", "wscript.exe") by Processes.dest Processes.user
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Processes.parent_process Processes.process_name Processes.process Processes.process_id
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Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`
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| `security_content_ctime(lastTime)` | `winword_spawning_windows_script_host_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: There will be limited false positives and it will be different
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for every environment. Tune by child process or command-line as needed.
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references:
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- https://attack.mitre.org/techniques/T1566/001/
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tags:
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analytic_story:
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- Spearphishing Attachments
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- CVE-2023-21716 Word RTF Heap Corruption
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asset_type: Endpoint
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confidence: 100
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impact: 70
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message: User $user$ on $dest$ spawned Windows Script Host from Winword.exe
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mitre_attack_id:
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- T1566
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- T1566.001
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observable:
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- name: dest
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type: Endpoint
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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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- Victim
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- name: process_name
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type: Process
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role:
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- Target
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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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required_fields:
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- _time
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- process_name
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- process_id
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- parent_process_name
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- dest
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- user
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- parent_process_id
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risk_score: 70
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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/T1566.001/macro/windows-sysmon_wsh.log
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source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
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sourcetype: xmlwineventlog
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