This analytic identifies Get-DomainTrust from PowerView in order to gather domain trust information. Typically, this is utilized within a script being executed and used to enumerate the domain trust information. This grants the adversary an understanding of how large or small the domain is. During triage, review parallel processes using an EDR product or 4688 events. It will be important to understand the timeline of events around this activity.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-08-24
- Author: Michael Haag, Splunk
- ID: 4fa7f846-054a-11ec-a836-acde48001122
Kill Chain Phase
1 2 3 4 5 6 | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process=*get-domaintrust* 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)` | `get_domaintrust_with_powershell_filter`
The SPL above uses the following Macros:
get-domaintrust_with_powershell_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
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
Processes 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
Limited false positives as this requires an active Administrator or adversary to bring in, import, and execute.
Associated Analytic Story
|12.0||30||40||Suspicious PowerShell Get-DomainTrust was identified on endpoint $dest$ by user $user$.|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
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