Detection: Splunk Unauthenticated DoS via Null Pointer References

Updated Date: 2024-07-01 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.

Search

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	Supported App
Splunk	Splunk	`'splunkd_ui_access'`	`'splunkd_ui_access.log'`	N/A

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

Splunk Vulnerabilities

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

https://advisory.splunk.com/advisories/SVD-2024-0702

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: 1