Detection: Splunk Unauthenticated DoS via Null Pointer References

Updated Date: 2024-10-17 ID: d67594fe-c317-41b8-9319-ec8428d5c2ea Author: Rod Soto Type: Hunting Product: Splunk Enterprise Security

Description

The following hunting search provides information on splunkd crash as a result of a Denial of Service Exploitation via null pointer references which targets 'services/cluster/config' endpoint.

1`splunk_crash_log` "Segmentation fault" "POST /services/cluster/config" 
2| stats count min(_time) as firstTime max(_time) as  lastTime by host 
3| `security_content_ctime(firstTime)` 
4| `security_content_ctime(lastTime)` 
5| `splunk_unauthenticated_dos_via_null_pointer_references_filter`

Data Source

Name Platform Sourcetype Source
Splunk Splunk icon Splunk 'splunkd_ui_access' 'splunkd_ui_access.log'

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
splunk_unauthenticated_dos_via_null_pointer_references_filter search *
splunk_unauthenticated_dos_via_null_pointer_references_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
T1499 Endpoint Denial of Service Impact
KillChainPhase.ACTIONS_ON_OBJECTIVES
NistCategory.DE_AE
Cis18Value.CIS_10
Sandworm Team

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

Requires access to internal indexes.

Known False Positives

This is a hunting search and will produce false positives. An operator needs to find proximity and detail of requests targeting cluster config endpoint and subsequent Segmentation fault in splunk crash log.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Possible exploitation attack against $host$ 50 100 50
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 ✅ Passing N/A N/A N/A
Unit ✅ Passing Dataset /opt/splunk/var/log/splunk/crash-*.log splunkd_crash_log
Integration ✅ Passing Dataset /opt/splunk/var/log/splunk/crash-*.log splunkd_crash_log

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: 2