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Description

This is a hunting search that provides elements to find possible dashboards created with external URL references in order to elicit Server Side Request Forgery from /data/ui/views endpoint.

  • Type: Hunting

  • Product: Splunk Enterprise

  • Last Updated: 2024-07-01
  • Author: Rod Soto, Chase Franklin
  • ID: b0a67520-ae82-4cf6-b04e-9f6cce56830d

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_web` user=* uri_path="/*/manager/permissions/launcher/data/ui/views/*" file=* 
| stats count min(_time) as firstTime max(_time) as lastTime by clientip user file host method uri_path uri_query 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `splunk_xss_via_external_urls_in_dashboards_ssrf_filter`

Macros

The SPL above uses the following Macros:

:information_source: splunk_xss_via_external_urls_in_dashboards_ssrf_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.

  • uri_path
  • user
  • file
  • clientip

How To Implement

Requires access to internal indexes.

Known False Positives

This is a hunting search and requires an operator to search for specific indicators of Server Side Request Forgery attack against /data/ui/views. It is not possible to grab display the payloads of such requests, so this search provides users, ip addresses, requests, files, and queries that may indicate malicious intent. There will be false positives.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
5.0 10 50 Possible SSRF attack 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: 1