Detection rules › Splunk

Windows Theme File Creation in Unusual Location

Status
production
Severity
low
Group by
CreationUtcTime, computer_name, event_action, file_name, process_guid, process_id, process_name, target_filename, user, vendor_product
Author
Raven Tait, Splunk
Source
github.com/splunk/security_content

Detects theme files being created in unusual locations. These files, used to customize desktop appearances, have been used for remote code execution and NTLM coercion attacks.

MITRE ATT&CK coverage

Event coverage

ProviderEventTitle
SysmonEvent ID 11FileCreate

Rule body splunk

name: Windows Theme File Creation in Unusual Location
id: a11f5f36-2c32-4323-8cb0-0fec84b3188d
version: 2
creation_date: '2021-09-02'
modification_date: '2026-05-13'
author: Raven Tait, Splunk
status: production
type: Anomaly
description: |-
    Detects theme files being created in unusual locations. These files, used to customize desktop appearances, have been used for remote code execution and NTLM coercion attacks.
data_source:
    - Sysmon EventID 11
search: |-
    | tstats `security_content_summariesonly`
      count min(_time) as firstTime
            max(_time) as lastTime
    
    from datamodel=Endpoint.Filesystem where
    
    Filesystem.file_path IN (
        "*\\Desktop\\*",
        "*\\Documents\\*",
        "*\\Downloads\\*",
        "*\\Temp\\*"
    )
    Filesystem.file_name="*.theme"
    Filesystem.action="created"
    
    by Filesystem.dest Filesystem.file_create_time Filesystem.process_path
       Filesystem.process_guid Filesystem.process_id Filesystem.file_path
       Filesystem.action Filesystem.file_name
       Filesystem.user Filesystem.vendor_product
    
    | `drop_dm_object_name(Filesystem)`
    | `security_content_ctime(firstTime)`
    | `security_content_ctime(lastTime)`
    | `windows_theme_file_creation_in_unusual_location_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: Legitimate customization or IT management may use theme files that trigger this detection. Review and allow trusted themes from authorized sources.
references:
    - https://www.darkreading.com/vulnerabilities-threats/recurring-windows-flaw-could-expose-user-credentials
drilldown_searches:
    - earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
      name: View the detection results for - "$user$" and "$dest$"
      search: '%original_detection_search% | search  user = "$user$" dest = "$dest$"'
    - 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: Windows theme file created in unusual location at $file_path$ on $dest$.
threat_objects:
    - field: file_path
      type: file_path
analytic_story:
    - Spearphishing Attachments
asset_type: Endpoint
mitre_attack_id:
    - T1187
    - T1557.001
    - T1021.002
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/T1187/snapattack/snapattack.log
          source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
          sourcetype: XmlWinEventLog
      test_type: unit

Stages and Predicates

Stage 1: tstats

| tstats `security_content_summariesonly`
  count min(_time) as firstTime
        max(_time) as lastTime

from datamodel=Endpoint.Filesystem where

Filesystem.file_path IN (
    "*\\Desktop\\*",
    "*\\Documents\\*",
    "*\\Downloads\\*",
    "*\\Temp\\*"
)
Filesystem.file_name="*.theme"
Filesystem.action="created"

by Filesystem.dest Filesystem.file_create_time Filesystem.process_path
   Filesystem.process_guid Filesystem.process_id Filesystem.file_path
   Filesystem.action Filesystem.file_name
   Filesystem.user Filesystem.vendor_product

Stage 2: search

| `drop_dm_object_name(Filesystem)`

Stage 3: search

| `security_content_ctime(firstTime)`

Stage 4: search

| `security_content_ctime(lastTime)`

Stage 5: search

| `windows_theme_file_creation_in_unusual_location_filter`

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

FieldKindValues
Filesystem.actioneq
  • "created" corpus 10 (splunk 10)
Filesystem.file_nameeq
  • "*.theme"
Filesystem.file_pathin
  • "*\\Desktop\\*"
  • "*\\Documents\\*"
  • "*\\Downloads\\*"
  • "*\\Temp\\*" corpus 4 (splunk 4)