System User Discovery With Query
This analytic looks for the execution of
query.exe with command-line arguments utilized to discover the logged user. Red Teams and adversaries alike may leverage
query.exe to identify system users on a compromised endpoint for situational awareness and Active Directory Discovery.
- Type: Hunting
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-09-13
- Author: Mauricio Velazco, Splunk
- ID: ad03bfcf-8a91-4bc2-a500-112993deba87
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_name="query.exe") (Processes.process=*user*) by Processes.dest Processes.user Processes.parent_process 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)` | `system_user_discovery_with_query_filter`
The SPL above uses the following Macros:
system_user_discovery_with_query_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
Known False Positives
Administrators or power users may use this command for troubleshooting.
Associated Analytic Story
|15.0||30||50||System user discovery on $dest$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
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: 1