Detection: Kerberos User Enumeration

Description

The following analytic detects an unusual number of Kerberos Ticket Granting Ticket (TGT) requests for non-existing users from a single source endpoint. It leverages Event ID 4768 and identifies anomalies using the 3-sigma statistical rule. This behavior is significant as it may indicate an adversary performing a user enumeration attack against Active Directory. If confirmed malicious, the attacker could validate a list of usernames, potentially leading to further attacks such as brute force or credential stuffing, compromising the security of the environment.

1`wineventlog_security` EventCode=4768 Status=0x6 TargetUserName!="*$" 
2| bucket span=2m _time 
3| stats dc(TargetUserName) AS unique_accounts values(TargetUserName) as tried_accounts by _time, src_ip 
4| eventstats avg(unique_accounts) as comp_avg , stdev(unique_accounts) as comp_std by src_ip 
5| eval upperBound=(comp_avg+comp_std*3) 
6| eval isOutlier=if(unique_accounts > 10 and unique_accounts >= upperBound, 1, 0) 
7| search isOutlier=1
8| `kerberos_user_enumeration_filter`

Data Source

Name Platform Sourcetype Source Supported App
Windows Event Log Security 4768 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Security' N/A

Macros Used

Name Value
wineventlog_security eventtype=wineventlog_security OR Channel=security OR source=XmlWinEventLog:Security
kerberos_user_enumeration_filter search *
kerberos_user_enumeration_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
T1589 Gather Victim Identity Information Reconnaissance
T1589.002 Email Addresses Reconnaissance
KillChainPhase.RECONNAISSANCE
NistCategory.DE_AE
Cis18Value.CIS_10
APT32
FIN13
HEXANE
LAPSUS$
Magic Hound
APT32
EXOTIC LILY
HAFNIUM
HEXANE
Kimsuky
LAPSUS$
Lazarus Group
Magic Hound
Sandworm Team
Silent Librarian
TA551

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

To successfully implement this search, you need to be ingesting Domain Controller and Kerberos events. The Advanced Security Audit policy setting Audit Kerberos Authentication Service within Account Logon needs to be enabled.

Known False Positives

Possible false positive scenarios include but are not limited to vulnerability scanners and missconfigured systems.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Potential Kerberos based user enumeration attack $src_ip$ 24 30 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: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: 4