Kibana ML Job Auth Escalation: CrossSpace Data Exposure
CVE-2026-78598 Published on September 2, 2026
Incorrect Authorization in Kibana Leading to Unauthorized Cross-Space Exposure of Machine Learning Job Data
Incorrect Authorization (CWE-863) in the Kibana machine learning feature can lead to information disclosure via Exploiting Incorrectly Configured Access Control Security Levels (CAPEC-180). An authenticated user holding machine learning job management privileges within a single Kibana space could cause a job's saved object to become accessible across all spaces in the Kibana instance, without holding access rights to those additional spaces.
Vulnerability Analysis
CVE-2026-78598 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 and integrity, and no impact on availability.
Weakness Type
What is an AuthZ Vulnerability?
The software performs an authorization check when an actor attempts to access a resource or perform an action, but it does not correctly perform the check. This allows attackers to bypass intended access restrictions.
CVE-2026-78598 has been classified to as an AuthZ vulnerability or weakness.
Products Associated with CVE-2026-78598
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Affected Versions
Elastic Kibana:- Version 8.0.0, <= 8.19.18 is affected.
- Version 9.0.0, <= 9.3.7 is affected.
- Version 9.4.0, <= 9.4.3 is affected.