Vulnerability from bitnami_vulndb
Published
2026-08-21 08:50
Modified
2026-08-21 09:11
Summary
MLflow: CreateModelVersion source validation does not check READ permission on referenced run_id
Details
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, CreateModelVersion accepts a run_id or model_id after _validate_source_run() or _validate_source_model() in mlflow/server/handlers.py verifies only path containment, allowing authenticated users to create a model version that references another user's artifact directory and read files through GET /model-versions/get-artifact without the required READ permission. This issue is fixed in version 3.15.0.
{
"affected": [
{
"package": {
"ecosystem": "Bitnami",
"name": "mlflow",
"purl": "pkg:bitnami/mlflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "3.15.0"
}
],
"type": "SEMVER"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N",
"type": "CVSS_V3"
}
]
}
],
"aliases": [
"CVE-2026-69148"
],
"database_specific": {
"cpes": [
"cpe:2.3:a:lfprojects:mlflow:*:*:*:*:*:node.js:*:*"
],
"severity": "High"
},
"details": "MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, CreateModelVersion accepts a run_id or model_id after _validate_source_run() or _validate_source_model() in mlflow/server/handlers.py verifies only path containment, allowing authenticated users to create a model version that references another user\u0027s artifact directory and read files through GET /model-versions/get-artifact without the required READ permission. This issue is fixed in version 3.15.0.",
"id": "BIT-mlflow-2026-69148",
"modified": "2026-08-21T09:11:01.118Z",
"published": "2026-08-21T08:50:13.561Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/mlflow/mlflow/commit/4bb7474771c3be808cd9e129defef9305f2869be"
},
{
"type": "WEB",
"url": "https://github.com/mlflow/mlflow/pull/24293"
},
{
"type": "WEB",
"url": "https://github.com/mlflow/mlflow/releases/tag/v3.15.0"
},
{
"type": "WEB",
"url": "https://github.com/mlflow/mlflow/security/advisories/GHSA-gqch-g4w5-7qcw"
},
{
"type": "WEB",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-69148"
}
],
"schema_version": "1.6.2",
"summary": "MLflow: CreateModelVersion source validation does not check READ permission on referenced run_id"
}
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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.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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