Detection: Rundll32 LockWorkStation

Description

The following analytic detects the execution of the rundll32.exe command with the user32.dll,LockWorkStation parameter, which is used to lock the workstation via command line. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as it is an uncommon method to lock a screen and has been observed in CONTI ransomware tooling for defense evasion. If confirmed malicious, this technique could indicate an attempt to evade detection and hinder incident response efforts.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=rundll32.exe Processes.process= "*user32.dll,LockWorkStation*" by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id Processes.parent_process_name 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `rundll32_lockworkstation_filter`

Data Source

Name Platform Sourcetype Source
CrowdStrike ProcessRollup2 N/A 'crowdstrike:events:sensor' 'crowdstrike'
Sysmon EventID 1 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'
Windows Event Log Security 4688 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Security'

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
rundll32_lockworkstation_filter search *
rundll32_lockworkstation_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
T1218 System Binary Proxy Execution Defense Evasion
T1218.011 Rundll32 Defense Evasion
KillChainPhase.EXPLOITAITON
NistCategory.DE_AE
Cis18Value.CIS_10
Lazarus Group
Volt Typhoon
APT19
APT28
APT3
APT32
APT38
APT41
Aquatic Panda
Blue Mockingbird
Carbanak
CopyKittens
Daggerfly
FIN7
Gamaredon Group
HAFNIUM
Kimsuky
Lazarus Group
LazyScripter
Magic Hound
MuddyWater
RedCurl
Sandworm Team
TA505
TA551
Wizard Spider

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 Risk Event True
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

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
Process $process_name$ with cmdline $process$ in host $dest$ 25 50 50
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: 4