Detection: Windows Cached Domain Credentials Reg Query

Description

The following analytic identifies a process command line querying the CachedLogonsCount registry value in the Winlogon registry. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions and registry queries. Monitoring this activity is significant as it can indicate the use of post-exploitation tools like Winpeas, which gather information about login caching settings. If confirmed malicious, this activity could help attackers understand login caching configurations, potentially aiding in credential theft or lateral movement within the network.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where  `process_reg` AND Processes.process = "* query *" AND Processes.process = "*\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Winlogon*" AND Processes.process = "*CACHEDLOGONSCOUNT*" by Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.process_guid Processes.parent_process_name Processes.parent_process Processes.parent_process_guid Processes.dest Processes.user 
3| `drop_dm_object_name(Processes)` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `windows_cached_domain_credentials_reg_query_filter`

Data Source

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

Macros Used

Name Value
process_reg (Processes.process_name=reg.exe OR Processes.original_file_name=reg.exe)
windows_cached_domain_credentials_reg_query_filter search *
windows_cached_domain_credentials_reg_query_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
T1003.005 Cached Domain Credentials Credential Access
T1003 OS Credential Dumping Credential Access
KillChainPhase.EXPLOITAITON
NistCategory.DE_AE
Cis18Value.CIS_10
APT33
Leafminer
MuddyWater
OilRig
APT28
APT32
APT39
Axiom
Leviathan
Poseidon Group
Sowbug
Suckfly
Tonto Team

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
a process with commandline $process$ tries to retrieve cache domain credential logon count in $dest$ 9 30 30
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: 2