CVE-2026-115292
Published:November 03, 2026
Updated:November 04, 2026
Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana Machine Learning can lead to information disclosure via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). An authenticated user with Machine Learning read access in one Kibana space can read the audit and error messages of data frame analytics jobs that belong to other spaces that the user is not authorized to access. These messages can include job details such as destination index names, analyzed field names, and failure information.
Affected Packages
https://github.com/elastic/kibana.git (GITHUB):
Affected version(s) >=v9.0.0 <v9.4.9Fix Suggestion:
Update to version v9.4.9https://github.com/elastic/kibana.git (GITHUB):
Affected version(s) >=v9.5.0 <v9.5.6Fix Suggestion:
Update to version v9.5.6https://github.com/elastic/kibana.git (GITHUB):
Affected version(s) >=v8.0.0 <v8.19.24Fix Suggestion:
Update to version v8.19.24Related Resources (2)
Do you need more information?
Contact UsCVSS v4
Base Score:
5.3
Attack Vector
NETWORK
Attack Complexity
LOW
Attack Requirements
NONE
Privileges Required
LOW
User Interaction
NONE
Vulnerable System Confidentiality
LOW
Vulnerable System Integrity
NONE
Vulnerable System Availability
NONE
Subsequent System Confidentiality
NONE
Subsequent System Integrity
NONE
Subsequent System Availability
NONE
CVSS v3
Base Score:
4.3
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
LOW
Integrity
NONE
Availability
NONE
Weakness Type (CWE)
Authorization Bypass Through User-Controlled Key