system_user_discovery_with_whoami.yml

name: System User Discovery With Whoami
id: 894fc43e-6f50-47d5-a68b-ee9ee23e18f4
version: 2
date: '2024-05-15'
author: Mauricio Velazco, Splunk
status: production
type: Hunting
description: The following analytic detects the execution of `whoami.exe` without
  any arguments. It leverages data from Endpoint Detection and Response (EDR) agents,
  focusing on process execution logs. This activity is significant because both Red
  Teams and adversaries use `whoami.exe` to identify the current logged-in user, aiding
  in situational awareness and Active Directory discovery. If confirmed malicious,
  this behavior could indicate an attacker is gathering information to further compromise
  the system, potentially leading to privilege escalation or lateral movement within
  the network.
data_source:
- Sysmon EventID 1
search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
  as lastTime from datamodel=Endpoint.Processes where (Processes.process_name="whoami.exe")
  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_whoami_filter`'
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: Administrators or power users may use this command for troubleshooting.
references:
- https://attack.mitre.org/techniques/T1033/
tags:
  analytic_story:
  - Winter Vivern
  - Active Directory Discovery
  - Rhysida Ransomware
  - Qakbot
  - CISA AA23-347A
  asset_type: Endpoint
  confidence: 50
  impact: 30
  message: System user discovery on $dest$
  mitre_attack_id:
  - T1033
  observable:
  - name: dest
    type: Endpoint
    role:
    - Victim
  product:
  - Splunk Enterprise
  - Splunk Enterprise Security
  - Splunk Cloud
  required_fields:
  - _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
  risk_score: 15
  security_domain: endpoint
tests:
- name: True Positive Test
  attack_data:
  - data: 
      https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1033/AD_discovery/windows-sysmon.log
    source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
    sourcetype: xmlwineventlog