Detection: Eventvwr UAC Bypass

Description

The following analytic detects an Eventvwr UAC bypass by identifying suspicious registry modifications in the path that Eventvwr.msc references upon execution. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on registry changes and process execution details. This activity is significant because it indicates a potential privilege escalation attempt, allowing an attacker to execute arbitrary commands with elevated privileges. If confirmed malicious, this could lead to unauthorized code execution, persistence, and further compromise of the affected system.

 1
 2| tstats `security_content_summariesonly` count min(_time) AS firstTime max(_time) AS lastTime FROM datamodel=Endpoint.Processes BY _time span=1h Processes.user Processes.process_id Processes.process_name Processes.process Processes.process_path Processes.dest Processes.parent_process_name Processes.parent_process Processes.process_guid 
 3| `drop_dm_object_name(Processes)` 
 4| join process_guid [ 
 5| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Registry WHERE (Registry.registry_path="*mscfile\\shell\\open\\command\\*") BY _time span=1h Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.registry_value_data Registry.process_guid 
 6| `drop_dm_object_name(Registry)`] 
 7| fields firstTime lastTime dest user parent_process_name parent_process process_name process_path process registry_key_name registry_path registry_value_name registry_value_data process_guid 
 8| where isnotnull(registry_value_data) 
 9| `security_content_ctime(firstTime)` 
10| `security_content_ctime(lastTime)` 
11| `eventvwr_uac_bypass_filter`

Data Source

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

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
eventvwr_uac_bypass_filter search *
eventvwr_uac_bypass_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
T1548.002 Bypass User Account Control Defense Evasion
T1548 Abuse Elevation Control Mechanism Privilege Escalation
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_10
APT29
APT37
BRONZE BUTLER
Cobalt Group
Earth Lusca
Evilnum
MuddyWater
Patchwork
Threat Group-3390

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

Some false positives may be present and will need to be filtered.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Registry values were modified to bypass UAC using Event Viewer on $dest$ by $user$. 80 80 100
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: 5