FKIE_CVE-2026-63145
Vulnerability from fkie_nvd - Published: 2026-07-21 23:18 - Updated: 2026-07-22 20:37
Severity
Summary
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.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "Kibana",
"vendor": "Elastic",
"versions": [
{
"lessThanOrEqual": "9.4.3",
"status": "affected",
"version": "9.4.0",
"versionType": "semver"
},
{
"lessThanOrEqual": "9.3.7",
"status": "affected",
"version": "9.0.0",
"versionType": "semver"
},
{
"lessThanOrEqual": "8.19.18",
"status": "affected",
"version": "8.0.0",
"versionType": "semver"
}
]
}
],
"source": "security@elastic.co"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "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).\n\nA vulnerability exists in Kibana\u0027s 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\u2014including jobs in other spaces or belonging to other users\u2014by leveraging Kibana\u0027s internally elevated credentials to write to restricted Machine Learning system indices that the user cannot access directly."
}
],
"id": "CVE-2026-63145",
"lastModified": "2026-07-22T20:37:38.603",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 4.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 1.4,
"source": "security@elastic.co",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-63145",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-07-22T13:20:48.112345Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-07-21T23:18:02.460",
"references": [
{
"source": "security@elastic.co",
"url": "https://discuss.elastic.co/t/kibana-8-19-19-9-3-8-9-4-4-security-update-esa-2026-69/388572"
}
],
"sourceIdentifier": "security@elastic.co",
"vulnStatus": "Awaiting Analysis",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-863"
}
],
"source": "security@elastic.co",
"type": "Secondary"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
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