CVE-2026-8147

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{"affected": [{"affectedData": [{"product": "mlflow/mlflow", "vendor": "mlflow", "versions": [{"lessThan": "3.14.0", "status": "affected", "version": "unspecified", "versionType": "custom"}]}], "source": "security@huntr.dev"}], "configurations": [{"nodes": [{"cpeMatch": [{"criteria": "cpe:2.3:a:lfprojects:mlflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "AD046C6D-0AF3-499E-A9D8-6BE7C0BEA278", "versionEndExcluding": "3.14.0", "vulnerable": true}], "negate": false, "operator": "OR"}]}], "cveTags": [], "descriptions": [{"lang": "en", "value": "In MLflow versions prior to 3.14.0, when running with authentication enabled, the trace API endpoints lack proper authorization validators. This allows any authenticated user to bypass experiment-level authorization controls on all trace operations, including reading, deleting, and modifying traces on experiments they do not have permission to access. The issue arises from the `_before_request` handler, which does not register authorization validators for trace endpoints, resulting in requests proceeding without validation. This vulnerability can expose sensitive data, destroy audit logs, and allow unauthorized modifications."}, {"lang": "es", "value": "En versiones de MLflow anteriores a la 3.14.0, cuando se ejecuta con la autenticaci\u00f3n habilitada, los puntos finales de la API de trazas carecen de validadores de autorizaci\u00f3n adecuados. Esto permite a cualquier usuario autenticado eludir los controles de autorizaci\u00f3n a nivel de experimento en todas las operaciones de traza, incluyendo la lectura, eliminaci\u00f3n y modificaci\u00f3n de trazas en experimentos a los que no tienen permiso de acceso. El problema surge del gestor \u2019_before_request\u2019, que no registra validadores de autorizaci\u00f3n para los puntos finales de traza, lo que resulta en que las solicitudes proceden sin validaci\u00f3n. Esta vulnerabilidad puede exponer datos sensibles, destruir registros de auditor\u00eda y permitir modificaciones no autorizadas."}], "id": "CVE-2026-8147", "lastModified": "2026-10-25T21:10:00.770", "metrics": {"cvssMetricV30": [{"cvssData": {"attackComplexity": "LOW", "attackVector": "NETWORK", "availabilityImpact": "NONE", "baseScore": 8.1, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N", "version": "3.0"}, "exploitabilityScore": 2.8, "impactScore": 5.2, "source": "security@huntr.dev", "type": "Secondary"}], "ssvcV203": [{"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "ssvcData": {"id": "CVE-2026-8147", "options": [{"exploitation": "poc"}, {"automatable": "no"}, {"technicalImpact": "total"}], "role": "CISA Coordinator", "timestamp": "2026-07-02T12:28:27.236676Z", "version": "2.0.3"}}]}, "published": "2026-07-02T09:16:19.100", "references": [{"source": "security@huntr.dev", "tags": ["Patch"], "url": "https://github.com/mlflow/mlflow/commit/f9b1eb510478570609ef451984a255775aa4b937"}, {"source": "security@huntr.dev", "tags": ["Exploit", "Third Party Advisory"], "url": "https://huntr.com/bounties/b00c3ddd-373e-492f-9bf0-41a28bb21ed5"}, {"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "tags": ["Exploit", "Third Party Advisory"], "url": "https://huntr.com/bounties/b00c3ddd-373e-492f-9bf0-41a28bb21ed5"}], "sourceIdentifier": "security@huntr.dev", "vulnStatus": "Analyzed", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-284"}], "source": "security@huntr.dev", "type": "Secondary"}, {"description": [{"lang": "en", "value": "NVD-CWE-noinfo"}], "source": "nvd@nist.gov", "type": "Primary"}]}

{"bugzilla": {"description": "mlflow: MLflow: Unauthorized access to trace data due to missing authorization validation", "id": "2496410", "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2496410"}, "csaw": false, "cvss3": {"cvss3_base_score": "8.1", "cvss3_scoring_vector": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N", "status": "draft"}, "cwe": "CWE-425", "details": ["In MLflow versions prior to 3.14.0, when running with authentication enabled, the trace API endpoints lack proper authorization validators. This allows any authenticated user to bypass experiment-level authorization controls on all trace operations, including reading, deleting, and modifying traces on experiments they do not have permission to access. The issue arises from the `_before_request` handler, which does not register authorization validators for trace endpoints, resulting in requests proceeding without validation. This vulnerability can expose sensitive data, destroy audit logs, and allow unauthorized modifications.", "A flaw was found in MLflow. When authentication is enabled, any authenticated user can bypass experiment-level authorization controls on trace API endpoints. This is due to missing authorization validators, allowing unauthorized reading, deleting, and modifying of traces. This vulnerability can lead to the exposure of sensitive data, destruction of audit logs, and unauthorized modifications to trace information."], "mitigation": {"lang": "en:us", "value": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability."}, "name": "CVE-2026-8147", "package_state": [{"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-mlflow-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-th06-cpu-torch210-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-th06-cuda130-torch210-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-th06-rocm64-torch291-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-training-cuda128-torch29-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-workbench-codeserver-datascience-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}], "public_date": "2026-07-02T07:32:58Z", "references": ["https://www.cve.org/CVERecord?id=CVE-2026-8147\nhttps://nvd.nist.gov/vuln/detail/CVE-2026-8147\nhttps://github.com/mlflow/mlflow/commit/f9b1eb510478570609ef451984a255775aa4b937\nhttps://huntr.com/bounties/b00c3ddd-373e-492f-9bf0-41a28bb21ed5"], "statement": "This Important flaw in MLflow, as deployed in Red Hat OpenShift AI, allows an authenticated user to bypass experiment-level authorization controls on trace API endpoints. This enables unauthorized access, modification, and deletion of sensitive trace data, impacting the confidentiality and integrity of machine learning experiment results within the platform. The vulnerability specifically affects the `rhoai/odh-mlflow-rhel9` component.", "threat_severity": "Important"}

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