As part of the sAMAccountName Spoofing (CVE-2021-42278) and Domain Controller Impersonation (CVE-2021-42287) exploitation chain, adversaries will request and obtain a Kerberos Service Ticket (TGS) with a domain controller computer account as the Service Name. This Service Ticket can be then used to take control of the domain controller on the final part of the attack. This analytic leverages Event Id 4769,
A Kerberos service ticket was requested, to identify an unusual TGS request where the Account_Name requesting the ticket matches the Service_Name field. This behavior could represent an exploitation attempt of CVE-2021-42278 and CVE-2021-42287 for privilege escalation.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-12-20
- Author: Mauricio Velazco, Splunk
- ID: 8b1297bc-6204-11ec-b7c4-acde48001122
Kill Chain Phase
1 2 3 4 5 `wineventlog_security` EventCode=4769 | eval isSuspicious = if(lower(Service_Name) = lower(mvindex(split(Account_Name,"@"),0)+"$"),1,0) | where isSuspicious = 1 | table _time, Client_Address, Account_Name, Service_Name, Failure_Code, isSuspicious | `suspicious_kerberos_service_ticket_request_filter`
The SPL above uses the following Macros:
suspicious_kerberos_service_ticket_request_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
We have tested this detection logic with ~2 million 4769 events and did not identify false positives. However, they may be possible in certain environments. Filter as needed.
Associated Analytic Story
|60.0||100||60||A suspicious Kerberos Service Ticket was requested by $Account_Name$|
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