CVE-2026-63145
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.
Matched ports (2)
| Port | Package | Version | Status | Maintainer |
|---|---|---|---|---|
| textproc/kibana91 | kibana91 | 9.1.10 | unaddressed | elastic@FreeBSD.org |
| textproc/kibana92 | kibana92 | 9.2.8 | unaddressed | elastic@FreeBSD.org |
Template for a VuXML entry
Range taken from the CVE record, check it before committing. make newentry in security/vuxml creates the vid.
<vuln vid="FIXME (make newentry)">
<topic>FIXME -- FIXME</topic>
<affects>
<package>
<name>kibana91</name>
<range><lt>8.19.19</lt></range>
</package>
<package>
<name>kibana92</name>
<range><lt>8.19.19</lt></range>
</package>
</affects>
<description>
<body xmlns="http://www.w3.org/1999/xhtml">
<p>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.</p>
</body>
</description>
<references>
<cvename>CVE-2026-63145</cvename>
<url>https://nvd.nist.gov/vuln/detail/CVE-2026-63145</url>
</references>
<dates>
<discovery>2026-07-21</discovery>
<entry>2026-10-26</entry>
</dates>
</vuln>