Detection: Unusual Number of Computer Service Tickets Requested

EXPERIMENTAL DETECTION

This detection status is set to experimental. The Splunk Threat Research team has not yet fully tested, simulated, or built comprehensive datasets for this detection. As such, this analytic is not officially supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2024-10-17 ID: ac3b81c0-52f4-11ec-ac44-acde48001122 Author: Mauricio Velazco, Splunk Type: Hunting Product: Splunk Enterprise Security

Description

The following analytic identifies an unusual number of computer service ticket requests from a single source, leveraging Event ID 4769, "A Kerberos service ticket was requested." It uses statistical analysis, including standard deviation and the 3-sigma rule, to detect anomalies in service ticket requests. This activity is significant as it may indicate malicious behavior such as lateral movement, malware staging, or reconnaissance. If confirmed malicious, an attacker could gain unauthorized access to multiple endpoints, facilitating further compromise and potential data exfiltration.

1`wineventlog_security` EventCode=4769 Service_Name="*$" Account_Name!="*$*" 
2| bucket span=2m _time 
3| stats dc(Service_Name) AS unique_targets values(Service_Name) as host_targets by _time, Client_Address, Account_Name 
4| eventstats avg(unique_targets) as comp_avg , stdev(unique_targets) as comp_std by Client_Address, Account_Name 
5| eval upperBound=(comp_avg+comp_std*3) 
6| eval isOutlier=if(unique_targets >10 and unique_targets >= upperBound, 1, 0) 
7| `unusual_number_of_computer_service_tickets_requested_filter`

Data Source

Name Platform Sourcetype Source
Windows Event Log Security 4769 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Security'

Macros Used

Name Value
wineventlog_security eventtype=wineventlog_security OR Channel=security OR source=XmlWinEventLog:Security
unusual_number_of_computer_service_tickets_requested_filter search *
unusual_number_of_computer_service_tickets_requested_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
T1078 Valid Accounts Defense Evasion
KillChainPhase.DELIVERY
KillChainPhase.EXPLOITAITON
KillChainPhase.INSTALLATION
NistCategory.DE_AE
Cis18Value.CIS_10
APT18
APT28
APT29
APT33
APT39
APT41
Akira
Axiom
Carbanak
Chimera
Cinnamon Tempest
Dragonfly
FIN10
FIN4
FIN5
FIN6
FIN7
FIN8
Fox Kitten
GALLIUM
INC Ransom
Indrik Spider
Ke3chang
LAPSUS$
Lazarus Group
Leviathan
OilRig
POLONIUM
PittyTiger
Play
Sandworm Team
Silence
Silent Librarian
Star Blizzard
Suckfly
Threat Group-3390
Volt Typhoon
Wizard Spider
menuPass

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 False
This configuration file applies to all detections of type hunting.

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

An single endpoint requesting a large number of computer service tickets is not common behavior. Possible false positive scenarios include but are not limited to vulnerability scanners, administration systeams and missconfigured systems.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
42 70 60
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 Not Applicable N/A N/A N/A
Unit ❌ Failing N/A N/A N/A
Integration ❌ Failing N/A N/A N/A

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