Detection: Windows Defacement Modify Transcodedwallpaper File

Updated Date: 2024-05-21 ID: e11c3d90-5bc7-42ad-94cd-ba75db10d897 Author: Teoderick Contreras, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic identifies modifications to the TranscodedWallpaper file in the wallpaper theme directory, excluding changes made by explorer.exe. This detection leverages the Endpoint.Processes and Endpoint.Filesystem data models to correlate process activity with file modifications. This activity is significant as it may indicate an adversary attempting to deface or change the desktop wallpaper of a targeted host, a tactic often used to signal compromise or deliver a message. If confirmed malicious, this could be a sign of unauthorized access and tampering, potentially leading to further system compromise or data exfiltration.

 1
 2| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.process_path !="*\\Windows\\Explorer.EXE" by _time span=1h Processes.process_id Processes.process_name Processes.process Processes.dest Processes.process_guid  Processes.original_file_name 
 3| `drop_dm_object_name(Processes)` 
 4|rename process_guid as proc_guid 
 5| join proc_guid, _time [ 
 6| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Filesystem where Filesystem.file_path = "*\\AppData\\Roaming\\Microsoft\\Windows\\Themes\\TranscodedWallpaper" by _time span=1h Filesystem.dest Filesystem.file_create_time Filesystem.file_name Filesystem.file_path Filesystem.process_guid 
 7| `drop_dm_object_name(Filesystem)` 
 8|rename process_guid as proc_guid 
 9| fields file_name file_path process_name process_path process dest file_create_time _time proc_guid] 
10| `windows_defacement_modify_transcodedwallpaper_file_filter`

Data Source

Name Platform Sourcetype Source Supported App
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike' N/A

Macros Used

Name Value
security_content_summariesonly summariesonly=summariesonly_config allow_old_summaries=oldsummaries_config fillnull_value=fillnull_config``
windows_defacement_modify_transcodedwallpaper_file_filter search *
windows_defacement_modify_transcodedwallpaper_file_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1491 Defacement Impact
KillChainPhase.ACTIONS_ON_OBJECTIVES
NistCategory.DE_AE
Cis18Value.CIS_10

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Risk Event True
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the Endpoint datamodel in the Filesystem node. In addition, confirm the latest CIM App 4.20 or higher is installed and the latest TA for the endpoint product.

Known False Positives

3rd part software application can change the wallpaper. Filter is needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
modification or creation of transcodedwallpaper file by $process_name$ in $dest$ 9 30 30
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation ✅ Passing N/A N/A N/A
Unit ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog
Integration ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

Source: GitHub | Version: 2