The following analytic leverages Event ID 4769,
A Kerberos service ticket was requested, to identify more than 30 computer service ticket requests from one source. When a domain joined endpoint connects to other remote endpoint, it will first request a Kerberos Service Ticket with the computer name as the Service Name. A user requesting a large number of computer service tickets for different endpoints could represent malicious behavior like lateral movement, malware staging, reconnaissance, etc.
Active Directory environments can be very different depending on the organization. Users should test this detection and customize the arbitrary threshold as needed.
- Type: Anomaly
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2023-03-20
- Author: Mauricio Velazco, Splunk
- ID: 386ad394-c9a7-4b4f-b66f-586252de20f0
Kill Chain Phase
- CIS 10
1 2 3 4 5 `wineventlog_security` EventCode=4769 ServiceName="*$" TargetUserName!="*$" | bucket span=5m _time | stats dc(ServiceName) AS unique_targets values(ServiceName) as host_targets by _time, IpAddress, TargetUserName | where unique_targets > 30 | `windows_large_number_of_computer_service_tickets_requested_filter`
The SPL above uses the following Macros:
windows_large_number_of_computer_service_tickets_requested_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
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 kerberos service tickets is not common behavior. Possible false positive scenarios include but are not limited to vulnerability scanners, administration systems and missconfigured systems.
Associated Analytic Story
|30.0||60||50||A large number of kerberos computer service tickets were requested by $IpAddress$ within 5 minutes.|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 1