Kibana ML ACL Bypass -> Cross-Space Audit Log Disclosure
CVE-2026-115292 Published on November 3, 2026

Authorization Bypass Through User-Controlled Key in Kibana Leading to Information Disclosure
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.

NVD

Vulnerability Analysis

CVE-2026-115292 is exploitable with network access, and requires small amount of user privileges. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to have a small impact on confidentiality, a small impact on integrity and availability.

Attack Vector:
NETWORK
Attack Complexity:
LOW
Privileges Required:
LOW
User Interaction:
NONE
Scope:
UNCHANGED
Confidentiality Impact:
LOW
Integrity Impact:
NONE
Availability Impact:
NONE

Weakness Type

What is an Insecure Direct Object Reference / IDOR Vulnerability?

The system's authorization functionality does not prevent one user from gaining access to another user's data or record by modifying the key value identifying the data.

CVE-2026-115292 has been classified to as an Insecure Direct Object Reference / IDOR vulnerability or weakness.


Products Associated with CVE-2026-115292

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Affected Versions

Elastic Kibana: