:warning: THIS IS A EXPERIMENTAL DETECTION

This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.

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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.

  • Type: Hunting
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2024-05-25
  • Author: Mauricio Velazco, Splunk
  • ID: ac3b81c0-52f4-11ec-ac44-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1078 Valid Accounts Defense Evasion, Persistence, Privilege Escalation, Initial Access
Kill Chain Phase
  • Exploitation
  • Installation
  • Delivery
NIST
  • DE.AE
CIS20
  • CIS 10
CVE
1
2
3
4
5
6
7
 `wineventlog_security` EventCode=4769 Service_Name="*$" Account_Name!="*$*" 
| bucket span=2m _time 
| stats dc(Service_Name) AS unique_targets values(Service_Name) as host_targets by _time, Client_Address, Account_Name 
| eventstats avg(unique_targets) as comp_avg , stdev(unique_targets) as comp_std by Client_Address, Account_Name 
| eval upperBound=(comp_avg+comp_std*3) 
| eval isOutlier=if(unique_targets >10 and unique_targets >= upperBound, 1, 0) 
| `unusual_number_of_computer_service_tickets_requested_filter`

Macros

The SPL above uses the following Macros:

:information_source: unusual_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.

Required fields

List of fields required to use this analytic.

  • _time
  • EventCode
  • Ticket_Options
  • Ticket_Encryption_Type
  • dest
  • service
  • service_id

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 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

RBA

Risk Score Impact Confidence Message
42.0 70 60  

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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 | version: 2