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Description

This analytic looks for the execution of wmic.exe with command-line arguments utilized to query for local users. The argument useraccount is used to leverage WMI to return a list of all local users. Red Teams and adversaries alike use net.exe to enumerate users for situational awareness and Active Directory Discovery.

  • Type: Hunting
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Endpoint
  • Last Updated: 2021-09-16
  • Author: Mauricio Velazco, Splunk
  • ID: 4902d7aa-0134-11ec-9d65-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1087 Account Discovery Discovery
T1087.001 Local Account Discovery
Kill Chain Phase
  • Exploitation
NIST
  • DE.AE
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 `process_wmic` (Processes.process=*useraccount*) 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)` 
| `local_account_discovery_with_wmic_filter`

Macros

The SPL above uses the following Macros:

:information_source: local_account_discovery_with_wmic_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

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.

Known False Positives

Administrators or power users may use this command for troubleshooting.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
15.0 30 50 Local user discovery enumeration on $dest$ by $user$

: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: 2