Windows TOR Client Execution

SPLUNK detection rule by Vignesh Subramanian, Splunk · Apache-2.0

The following analytic detects the execution of the TOR Browser and related TOR components on Windows endpoints by monitoring process creation activity. Adversaries and insider threats leverage TOR to anonymize command-and-control traffic, facilitate data exfiltration, and evade network monitoring and policy enforcement. While TOR can be used for legitimate research and privacy purposes, its presence on enterprise endpoints is often unusual and should be investigated to determine intent, scope, and any associated malicious behavior.

name: Windows TOR Client Execution
id: f164bc6f-ecbe-45e0-aaa6-f5c4d8c84b9a
version: 4
creation_date: '2026-02-02'
modification_date: '2026-05-13'
author: Vignesh Subramanian, Splunk
status: production
type: Anomaly
description: |
    The following analytic detects the execution of the TOR Browser and related TOR components on Windows endpoints by monitoring process creation activity.
    Adversaries and insider threats leverage TOR to anonymize command-and-control traffic, facilitate data exfiltration, and evade network monitoring and policy enforcement.
    While TOR can be used for legitimate research and privacy purposes, its presence on enterprise endpoints is often unusual and should be investigated to determine intent, scope, and any associated malicious behavior.
data_source:
    - CrowdStrike ProcessRollup2
    - Sysmon EventID 1
    - Windows Event Log Security 4688
search: |
    | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime
      from datamodel=Endpoint.Processes where
      (
        Processes.process_name = "tor.exe"
        OR
        (
          Processes.process_path = "*\\BraveSoftware\\Brave-Browser*"
          Processes.process_path = "*\\tor-*"
        )
      )
      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_tor_client_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: |
    This detection focuses on TOR-related processes and may generate benign matches in environments where TOR is intentionally used, such as security testing, research, or lab environments.
references:
    - https://unit42.paloaltonetworks.com/tor-traffic-enterprise-networks/
    - https://attack.mitre.org/software/S0183/
    - https://attack.mitre.org/techniques/T1090/003/
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 ("$user$", "$dest$") | 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: 7d
      latest_offset: "0"
intermediate_findings:
    entities:
        - field: dest
          type: system
          score: 20
          message: TOR client process $process_name$ was launched by parent process $parent_process_name$ on host $dest$ by the user $user$ with command line $process$
        - field: user
          type: user
          score: 20
          message: TOR client process $process_name$ was launched by parent process $parent_process_name$ on host $dest$ by the user $user$ with command line $process$
threat_objects:
    - field: parent_process_name
      type: parent_process_name
    - field: process
      type: process
    - field: process_name
      type: process_name
analytic_story:
    - Compromised Windows Host
    - Windows Post-Exploitation
    - Command And Control
    - Data Exfiltration
    - Data Protection
asset_type: Endpoint
mitre_attack_id:
    - T1090.003
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: endpoint
security_domain: endpoint
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1090.003/windows_tor_client_execution/windows-sysmon.log
          sourcetype: XmlWinEventLog
          source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
      test_type: unit

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Executable code, not a declarative rule

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Format & documentation suggestions

Not a security issue — this rule is valid and was accepted as-is. These are optional fields/conventions its own format recommends, mainly affecting its quality score and how well it documents itself for other reviewers.

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