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Description

The following analytic identifies potential exploitation of a Cross-Site Scripting (XSS) vulnerability in Splunk Enterprise 9.1.2. It detects suspicious requests to the Splunk web GUI that may execute JavaScript within script tags. This detection leverages logs from the splunkd_ui data source, focusing on specific URI paths and HTTP methods. This activity is significant as it can allow attackers to execute arbitrary JavaScript, potentially accessing the API with the logged-in user's permissions. If the user is an admin, the attacker could create an admin account, leading to full control over the Splunk environment.

  • Type: Hunting

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2024-07-01
  • Author: Rod Soto, Splunk
  • ID: 1030bc63-0b37-4ac9-9ae0-9361c955a3cc

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1189 Drive-by Compromise Initial Access
Kill Chain Phase
  • Delivery
NIST
  • DE.AE
CIS20
  • CIS 10
CVE
ID Summary CVSS
    


1
2
3
4
5



`splunkd_ui` "/*/splunkd/__raw/servicesNS/nobody/search/authentication/users" status=201 
| stats count min(_time) as firstTime max(_time) as lastTime by clientip, uri_path, method 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `splunk_xss_in_highlighted_json_events_filter`

Macros

The SPL above uses the following Macros:

:information_source: splunk_xss_in_highlighted_json_events_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • clientip
  • uri_path
  • method
  • status

How To Implement

This search only applies to web-GUI-enabled Splunk instances and operator must have access to internal indexes.

Known False Positives

This is a hunting search and will produce false positives as it is not possible to view contents of a request payload. It shows the artifact resulting from a potential exploitation payload (the creation of a user with admin privileges).

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
15.0 30 50 Possible XSS exploitation from $clientip$

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

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 | version: 3