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Description

The following analytic detects arbitrary command execution using Windows msdt.exe, a Diagnostics Troubleshooting Wizard. It leverages Endpoint Detection and Response (EDR) data to identify instances where msdt.exe is invoked via the ms-msdt:/ protocol handler to retrieve a remote payload. This activity is significant as it can indicate an exploitation attempt leveraging msdt.exe to execute arbitrary commands, potentially leading to unauthorized code execution. If confirmed malicious, this could allow an attacker to execute arbitrary code, escalate privileges, or persist within the environment, posing a severe security risk.

  • Type: TTP
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2024-05-19
  • Author: Michael Haag, Teoderick Contreras, Splunk
  • ID: e1d5145f-38fe-42b9-a5d5-457796715f97

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1218 System Binary Proxy Execution Defense Evasion
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 10
CVE 


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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=msdt.exe Processes.process IN ("*msdt*","*ms-msdt:*","*ms-msdt:/id*","*ms-msdt:-id*","*/id*") AND (Processes.process="*IT_BrowseForFile=*" OR Processes.process="*IT_RebrowseForFile=*" OR Processes.process="*.xml*") AND Processes.process="*PCWDiagnostic*" by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.process Processes.process_id Processes.parent_process_id 
| `drop_dm_object_name(Processes)` 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)`
| `windows_execute_arbitrary_commands_with_msdt_filter`

Macros

The SPL above uses the following Macros:

:information_source: windows_execute_arbitrary_commands_with_msdt_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • Processes.dest
  • Processes.user
  • Processes.parent_process_name
  • Processes.parent_process
  • Processes.original_file_name
  • Processes.process_name
  • Processes.process
  • Processes.process_id
  • Processes.parent_process_path
  • Processes.process_path
  • Processes.parent_process_id

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

False positives may be present, filter as needed. Added .xml to potentially capture any answer file usage. Remove as needed.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
100.0 100 100 A parent process $parent_process_name$ has spawned a child process $process_name$ on host $dest$ possibly indicative of indirect command execution.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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 | version: 4