Detection: Wermgr Process Spawned CMD Or Powershell Process

Description

The following analytic detects the spawning of cmd or PowerShell processes by the wermgr.exe process. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process telemetry, including parent-child process relationships and command-line executions. This behavior is significant as it is commonly associated with code injection techniques used by malware like TrickBot to execute shellcode or malicious DLL modules. If confirmed malicious, this activity could allow attackers to execute arbitrary code, escalate privileges, or maintain persistence within the environment, posing a severe threat to system security.

1
2| tstats `security_content_summariesonly` values(Processes.process) as cmdline min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name = "wermgr.exe" `process_cmd` OR `process_powershell` by Processes.parent_process_name  Processes.original_file_name Processes.parent_process_id  Processes.process_name Processes.process Processes.process_id Processes.process_guid Processes.dest Processes.user 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `wermgr_process_spawned_cmd_or_powershell_process_filter`

Data Source

Name Platform Sourcetype Source Supported App
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike' N/A

Macros Used

Name Value
process_cmd (Processes.process_name=cmd.exe OR Processes.original_file_name=Cmd.Exe)
wermgr_process_spawned_cmd_or_powershell_process_filter search *
wermgr_process_spawned_cmd_or_powershell_process_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1059 Command and Scripting Interpreter Execution
KillChainPhase.INSTALLATION
NistCategory.DE_CM
Cis18Value.CIS_10
APT19
APT32
APT37
APT39
Dragonfly
FIN5
FIN6
FIN7
Fox Kitten
Ke3chang
OilRig
Stealth Falcon
Whitefly
Windigo

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

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

unknown

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Wermgr.exe spawning suspicious processes on $dest$ 56 70 80
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Passing N/A N/A N/A
Unit Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog
Integration ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational xmlwineventlog

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: GitHub | Version: 3