ID | Technique | Tactic |
---|---|---|
T1558.003 | Kerberoasting | Credential Access |
Detection: ServicePrincipalNames Discovery with SetSPN
Description
The following analytic detects the use of setspn.exe
to query the domain for Service Principal Names (SPNs). This detection leverages Endpoint Detection and Response (EDR) data, focusing on specific command-line arguments associated with setspn.exe
. Monitoring this activity is crucial as it often precedes Kerberoasting or Silver Ticket attacks, which can lead to credential theft. If confirmed malicious, an attacker could use the gathered SPNs to escalate privileges or persist within the environment, posing a significant security risk.
Search
1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where `process_setspn` (Processes.process="*-t*" AND Processes.process="*-f*") OR (Processes.process="*-q*" AND Processes.process="**/**") OR (Processes.process="*-q*") OR (Processes.process="*-s*") by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id
3| `drop_dm_object_name(Processes)`
4| `security_content_ctime(firstTime)`
5| `security_content_ctime(lastTime)`
6| `serviceprincipalnames_discovery_with_setspn_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
CrowdStrike ProcessRollup2 | N/A | 'crowdstrike:events:sensor' |
'crowdstrike' |
N/A |
Macros Used
Name | Value |
---|---|
process_setspn | (Processes.process_name=setspn.exe OR Processes.original_file_name=setspn.exe) |
serviceprincipalnames_discovery_with_setspn_filter | search * |
serviceprincipalnames_discovery_with_setspn_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
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 Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
Creates Risk Event | True |
Implementation
The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Processes
node of the Endpoint
data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.
Known False Positives
False positives may be caused by Administrators resetting SPNs or querying for SPNs. Filter as needed.
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest$ by user $user$ attempting to identify service principle names. | 80 | 80 | 100 |
References
-
https://docs.microsoft.com/en-us/windows/win32/ad/service-principal-names
-
https://strontic.github.io/xcyclopedia/library/setspn.exe-5C184D581524245DAD7A0A02B51FD2C2.html
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
xmlwineventlog |
Integration | ✅ Passing | Dataset | XmlWinEventLog:Microsoft-Windows-Sysmon/Operational |
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: 3