GitHub Repo

Detection: Splunk Unauthorized Experimental Items Creation

REMOVED DETECTION

This detection has been removed from the Splunk Threat Research content library and is no longer maintained or supported.

Reason: Detection is deprecated as the associated CVEs have been patched in the latest Splunk release.

Removed in version: 5.6.0

If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2026-05-14 ID: 84afda04-0cd6-466b-869e-70d6407d0a34 Author: Rod Soto, Chase Franklin Type: Hunting Product: Splunk Enterprise Security

Description

This hunting search provides information on finding possible creation of unauthorized items against /experimental endpoint.

1`splunkda` */experimental/* method=POST 
2| stats count min(_time) as firstTime max(_time) as lastTime by clientip method uri_path uri status 
3| `security_content_ctime(firstTime)` 
4| `security_content_ctime(lastTime)` 
5| `splunk_unauthorized_experimental_items_creation_filter`

Data Source

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

Macros Used

Name Value
splunkda index=_internal sourcetype=splunkd_access
splunk_unauthorized_experimental_items_creation_filter ``
splunk_unauthorized_experimental_items_creation_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
T1189 Drive-by Compromise Initial Access

CVE

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule N/A
Earliest Time N/A
Latest Time N/A
Schedule Window N/A
Creates Finding (Notable) No
Creates Intermediate Finding (Risk Event) No
Hunting detections do not generate a Finding (Notable) or Intermediate Findings (Risk Events).

Implementation

Requires access to internal indexes.

Known False Positives

Not all requests are going to be malicious, there will be false positives, however operator must find suspicious items that might have been created by an unauthorized user.

Associated Analytic Story

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Not Applicable N/A N/A N/A
Unit Not Applicable N/A N/A N/A

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: 5