Missing Authorization in Kibana Leading to Unauthorized Modification of Machine Learning Trained Model Space Assignments
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
| Vendor | Product | Default status | Versions | |||||||||
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| Elastic | Kibana | unaffected |
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Configuration 1 [-]
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No data.
| Vendor | Product | Versions | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Elastic | Kibana |
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No CVSS v4.0
No CVSS v3.0
No CVSS v2
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.268% probability within 30 days)
| Type | Values Removed | Values Added |
|---|---|---|
| CPEs | cpe:2.3:a:elastic:kibana:*:*:*:*:*:*:*:* |
| Type | Values Removed | Values Added |
|---|---|---|
| First Time appeared |
Elastic
Elastic kibana |
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| Vendors & Products |
Elastic
Elastic kibana |
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| Metrics |
ssvc
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| Type | Values Removed | Values Added |
|---|---|---|
| Description | A Kibana Machine Learning capability that removes a saved object from the current space accepts machine learning trained models as a target, but it verifies only the privileges that apply to anomaly detection jobs and data frame analytics jobs. A user whose role grants create anomaly detection jobs and data frame analytics jobs without the trained model privilege can therefore remove a trained model from a space. The model itself is not deleted and remains available in its other spaces, and the change can be reversed by a suitably privileged user. | |
| Title | Missing Authorization in Kibana Leading to Unauthorized Modification of Machine Learning Trained Model Space Assignments | |
| Weaknesses | CWE-862 | |
| References |
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| Metrics |
cvssV3_1
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