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BIT-elk-2026-63145

Published Jul 28, 2026·Last modified Jul 28, 2026
Affected Components(0)

No affected components available

Description

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.

Risk Scores
Base Score
0.0

Measures severity based on intrinsic characteristics of the vulnerability, independent of environment.

Threat Intelligence
0.0

No exploitation activity has been observed at this time. Continue routine monitoring.

EPSS
N/A

Probability that this vulnerability will be exploited in the wild within the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

Related Vulnerabilities
  • EUVD-2026-47584
    Alias
  • CVE-2026-63145
    Alias
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