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CVE-2026-63145
Published:July 21, 2026
Updated:August 05, 2026
Incorrect Authorization (CWE-863) in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management endpoint performs an insufficient authorization check. The endpoint validates only a coarse privilege level but does not verify that the requesting user has access to the specific Machine Learning job or notification resources provided in the request. As a result, a low-privileged user with Machine Learning access in any Kibana space can manipulate Machine Learning audit and notification records for arbitrary jobs—including jobs in other spaces or belonging to other users—by leveraging Kibana's internally elevated credentials to write to restricted Machine Learning system indices that the user cannot access directly.
Affected Packages
https://github.com/elastic/kibana.git (GITHUB):
Affected version(s) >=v8.0.0 <v8.19.19
Fix Suggestion:
Update to version v8.19.19
https://github.com/elastic/kibana.git (GITHUB):
Affected version(s) >=v9.0.0 <v9.3.8
Fix Suggestion:
Update to version v9.3.8
https://github.com/elastic/kibana.git (GITHUB):
Affected version(s) >=v9.4.0 <v9.4.4
Fix Suggestion:
Update to version v9.4.4
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CVSS v4
Base Score:
5.3
Attack Vector
NETWORK
Attack Complexity
LOW
Attack Requirements
NONE
Privileges Required
LOW
User Interaction
NONE
Vulnerable System Confidentiality
NONE
Vulnerable System Integrity
LOW
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
NONE
Integrity
LOW
Availability
NONE
Weakness Type (CWE)
Incorrect Authorization
EPSS
Base Score:
0.16