mirror of
https://github.com/splunk/security_content
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Bhavin Patel
88 lines
3.5 KiB
YAML
88 lines
3.5 KiB
YAML
name: Excel Spawning Windows Script Host
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id: 57fe880a-9be3-11eb-9bf3-acde48001122
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version: 3
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date: '2024-05-20'
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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 Excel spawns
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Windows Script Host processes (`cscript.exe` or `wscript.exe`). This behavior is
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detected using Endpoint Detection and Response (EDR) telemetry, focusing on process
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creation events where the parent process is `excel.exe`. This activity is significant
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because it is uncommon and often associated with malicious actions, such as spearphishing
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attacks. If confirmed malicious, this could allow an attacker to execute scripts,
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potentially leading to code execution, data exfiltration, or further system compromise.
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Immediate investigation and mitigation are recommended.
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data_source:
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- Sysmon EventID 1
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search: '| tstats `security_content_summariesonly` count values(Processes.process)
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min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes
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where Processes.parent_process_name="excel.exe" Processes.process_name IN ("cscript.exe",
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"wscript.exe") by Processes.parent_process Processes.parent_process_name Processes.process_name
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Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`
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| `excel_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: False positives should be limited, but if any are present,
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filter as needed. In some instances, `cscript.exe` is used for legitimate business
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practices.
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references:
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- https://app.any.run/tasks/8ecfbc29-03d0-421c-a5bf-3905d29192a2/
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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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asset_type: Endpoint
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confidence: 100
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impact: 80
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message: An instance of $parent_process_name$ spawning $process_name$ was identified
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on endpoint $dest$ by user $user$, indicating potential suspicious macro execution.
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mitre_attack_id:
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- T1003.002
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- T1003
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observable:
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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: dest
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type: Hostname
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role:
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- Victim
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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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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: 80
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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.log
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source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
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sourcetype: xmlwineventlog
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