CVE-2026-63145: CWE-863 Incorrect Authorization in Elastic Kibana
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.
AI Analysis
Technical Summary
This vulnerability in Kibana arises from an incorrect authorization check (CWE-863) in a Machine Learning management endpoint. The endpoint validates only a broad privilege level but fails to verify that the user has permission to access the specific Machine Learning job or notification resource referenced in the request. Consequently, a low-privileged user with Machine Learning access in any Kibana space can exploit Kibana's internally elevated credentials to write to restricted Machine Learning system indices. This allows manipulation of audit and notification records for arbitrary jobs, including those in other spaces or owned by other users. No official patch or remediation level is indicated in the available data.
Potential Impact
The vulnerability allows low-privileged users with Machine Learning access to modify audit and notification records of arbitrary Machine Learning jobs across different spaces and users. This compromises the integrity of these records but does not impact confidentiality or availability. There are no known exploits in the wild. The impact is limited to integrity loss of Machine Learning audit and notification data.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until an official fix is available, restrict Machine Learning access to trusted users only. Monitor for unusual modifications to Machine Learning audit and notification records. Follow Elastic's official advisories for updates on remediation.
CVE-2026-63145: CWE-863 Incorrect Authorization in Elastic Kibana
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.
CVSS v3.1
Score 4.3medium
Affected software
pkg:github/elastic/kibanaRun on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
This vulnerability in Kibana arises from an incorrect authorization check (CWE-863) in a Machine Learning management endpoint. The endpoint validates only a broad privilege level but fails to verify that the user has permission to access the specific Machine Learning job or notification resource referenced in the request. Consequently, a low-privileged user with Machine Learning access in any Kibana space can exploit Kibana's internally elevated credentials to write to restricted Machine Learning system indices. This allows manipulation of audit and notification records for arbitrary jobs, including those in other spaces or owned by other users. No official patch or remediation level is indicated in the available data.
Potential Impact
The vulnerability allows low-privileged users with Machine Learning access to modify audit and notification records of arbitrary Machine Learning jobs across different spaces and users. This compromises the integrity of these records but does not impact confidentiality or availability. There are no known exploits in the wild. The impact is limited to integrity loss of Machine Learning audit and notification data.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until an official fix is available, restrict Machine Learning access to trusted users only. Monitor for unusual modifications to Machine Learning audit and notification records. Follow Elastic's official advisories for updates on remediation.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- elastic
- Date Reserved
- 2026-07-15T18:23:57.166Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a5ff8649c2644c7f8e52c89
Added to database: 07/21/2026, 22:53:24 UTC
Last enriched: 07/21/2026, 23:08:03 UTC
Last updated: 07/22/2026, 00:10:22 UTC
Views: 3
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