Detection: Windows Increase in Group or Object Modification Activity

Description

This analytic detects an increase in modifications to AD groups or objects. Frequent changes to AD groups or objects can indicate potential security risks, such as unauthorized access attempts, impairing defences or establishing persistence. By monitoring AD logs for unusual modification patterns, this detection helps identify suspicious behavior that could compromise the integrity and security of the AD environment.

1`wineventlog_security` EventCode IN (4670,4727,4731,4734,4735,4764) 
2| bucket span=5m _time  
3| stats values(object) as object, dc(object) as objectCount, values(src_user_category) as src_user_category, values(dest) as dest, values(dest_category) as dest_category by _time, src_user, signature, status 
4| eventstats avg(objectCount) as comp_avg, stdev(objectCount) as comp_std by src_user, signature 
5| eval upperBound=(comp_avg+comp_std) 
6| eval isOutlier=if(objectCount > 10 and (objectCount >= upperBound), 1, 0) 
7| search isOutlier=1  
8| `windows_increase_in_group_or_object_modification_activity_filter`

Data Source

Name Platform Sourcetype Source
Windows Event Log Security 4663 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Security'

Macros Used

Name Value
wineventlog_security eventtype=wineventlog_security OR Channel=security OR source=XmlWinEventLog:Security
windows_increase_in_group_or_object_modification_activity_filter search *
windows_increase_in_group_or_object_modification_activity_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
T1098 Account Manipulation Persistence
T1562 Impair Defenses Privilege Escalation
KillChainPhase.EXPLOITAITON
KillChainPhase.INSTALLATION
NistCategory.DE_CM
Cis18Value.CIS_10
HAFNIUM
Lazarus Group
Magic Hound

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

Run this detection looking over a 7 day timeframe for best results.

Known False Positives

Unknown

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Spike in Group or Object Modifications performed by $src_user$ 8 20 40
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Passing N/A N/A N/A
Unit Passing Dataset XmlWinEventLog:Security XmlWinEventLog
Integration ✅ Passing Dataset XmlWinEventLog:Security 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