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splunk_escuAnomaly
Windows WMI Process And Service List
The following analytic identifies suspicious WMI command lines querying for running processes or services. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific process and command-line events. This activity is significant as adversaries often use WMI to gather system information and identify services on compromised machines. If confirmed malicious, this behavior could allow attackers to map out the system, identify critical services, and plan further attacks, potentially leading to privilege escalation or persistence within the environment.
MITRE ATT&CK
Detection Query
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE `process_wmic` Processes.process IN ("*process*", "*service*") Processes.process = "*list*"
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_wmi_process_and_service_list_filter`Author
Teoderick Contreras, Splunk
Created
2026-03-10
Data Sources
Sysmon EventID 1Windows Event Log Security 4688CrowdStrike ProcessRollup2
References
Tags
Windows Post-ExploitationPrestige Ransomware
Raw Content
name: Windows WMI Process And Service List
id: ef3c5ef2-3f6d-4087-aa75-49bf746dc907
version: 9
date: '2026-03-10'
author: Teoderick Contreras, Splunk
status: production
type: Anomaly
description: The following analytic identifies suspicious WMI command lines querying for running processes or services. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific process and command-line events. This activity is significant as adversaries often use WMI to gather system information and identify services on compromised machines. If confirmed malicious, this behavior could allow attackers to map out the system, identify critical services, and plan further attacks, potentially leading to privilege escalation or persistence within the environment.
data_source:
- Sysmon EventID 1
- Windows Event Log Security 4688
- CrowdStrike ProcessRollup2
search: |-
| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes
WHERE `process_wmic` Processes.process IN ("*process*", "*service*") Processes.process = "*list*"
BY Processes.action Processes.dest Processes.original_file_name
Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid
Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path
Processes.process Processes.process_exec Processes.process_guid
Processes.process_hash Processes.process_id Processes.process_integrity_level
Processes.process_name Processes.process_path Processes.user
Processes.user_id Processes.vendor_product
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_wmi_process_and_service_list_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: netowrk administrator or IT may execute this command for auditing processes and services.
references:
- https://github.com/carlospolop/PEASS-ng/tree/master/winPEAS
- https://www.microsoft.com/en-us/security/blog/2022/10/14/new-prestige-ransomware-impacts-organizations-in-ukraine-and-poland/
drilldown_searches:
- name: View the detection results for - "$dest$"
search: '%original_detection_search% | search dest = "$dest$"'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
- name: View risk events for the last 7 days for - "$dest$"
search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
rba:
message: wmi command $process$ to list processes and services on $dest$
risk_objects:
- field: dest
type: system
score: 20
threat_objects: []
tags:
analytic_story:
- Windows Post-Exploitation
- Prestige Ransomware
asset_type: Endpoint
mitre_attack_id:
- T1047
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
security_domain: endpoint
tests:
- name: True Positive Test
attack_data:
- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/winpeas/sysmon.log
source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
sourcetype: XmlWinEventLog