{"dataType": "CVE_RECORD", "dataVersion": "5.2", "cveMetadata": {"cveId": "CVE-2026-8147", "assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a", "state": "PUBLISHED", "assignerShortName": "@huntr_ai", "dateReserved": "2026-05-08T02:45:28.857Z", "datePublished": "2026-07-02T07:32:58.308Z", "dateUpdated": "2026-07-02T12:28:31.554Z"}, "containers": {"cna": {"title": "Authorization Bypass in mlflow/mlflow", "providerMetadata": {"orgId": "c09c270a-b464-47c1-9133-acb35b22c19a", "shortName": "@huntr_ai", "dateUpdated": "2026-07-02T07:32:58.308Z"}, "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."}], "affected": [{"vendor": "mlflow", "product": "mlflow/mlflow", "versions": [{"version": "unspecified", "lessThan": "3.14.0", "status": "affected", "versionType": "custom"}]}], "references": [{"url": "https://huntr.com/bounties/b00c3ddd-373e-492f-9bf0-41a28bb21ed5"}, {"url": "https://github.com/mlflow/mlflow/commit/f9b1eb510478570609ef451984a255775aa4b937"}], "metrics": [{"cvssV3_0": {"version": "3.0", "attackComplexity": "LOW", "attackVector": "NETWORK", "availabilityImpact": "NONE", "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", "baseScore": 8.1, "baseSeverity": "HIGH"}}], "problemTypes": [{"descriptions": [{"type": "CWE", "lang": "en", "description": "CWE-284 Improper Access Control", "cweId": "CWE-284"}]}], "source": {"advisory": "b00c3ddd-373e-492f-9bf0-41a28bb21ed5", "discovery": "EXTERNAL"}}, "adp": [{"references": [{"url": "https://huntr.com/bounties/b00c3ddd-373e-492f-9bf0-41a28bb21ed5", "tags": ["exploit"]}], "metrics": [{"other": {"type": "ssvc", "content": {"timestamp": "2026-07-02T12:28:27.236676Z", "id": "CVE-2026-8147", "options": [{"Exploitation": "poc"}, {"Automatable": "no"}, {"Technical Impact": "total"}], "role": "CISA Coordinator", "version": "2.0.3"}}}], "title": "CISA ADP Vulnrichment", "providerMetadata": {"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "shortName": "CISA-ADP", "dateUpdated": "2026-07-02T12:28:31.554Z"}}]}}

{"dataType": "CVE_RECORD", "containers": {"adp": [{"title": "CISA ADP Vulnrichment", "metrics": [{"other": {"type": "ssvc", "content": {"id": "CVE-2026-8147", "role": "CISA Coordinator", "options": [{"Exploitation": "poc"}, {"Automatable": "no"}, {"Technical Impact": "total"}], "version": "2.0.3", "timestamp": "2026-07-02T12:28:27.236676Z"}}}], "references": [{"url": "https://huntr.com/bounties/b00c3ddd-373e-492f-9bf0-41a28bb21ed5", "tags": ["exploit"]}], "providerMetadata": {"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "shortName": "CISA-ADP", "dateUpdated": "2026-07-02T12:28:17.262Z"}}], "cna": {"title": "Authorization Bypass in mlflow/mlflow", "source": {"advisory": "b00c3ddd-373e-492f-9bf0-41a28bb21ed5", "discovery": "EXTERNAL"}, "metrics": [{"cvssV3_0": {"scope": "UNCHANGED", "version": "3.0", "baseScore": 8.1, "attackVector": "NETWORK", "baseSeverity": "HIGH", "vectorString": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N", "integrityImpact": "HIGH", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "NONE", "privilegesRequired": "LOW", "confidentialityImpact": "HIGH"}}], "affected": [{"vendor": "mlflow", "product": "mlflow/mlflow", "versions": [{"status": "affected", "version": "unspecified", "lessThan": "3.14.0", "versionType": "custom"}]}], "references": [{"url": "https://huntr.com/bounties/b00c3ddd-373e-492f-9bf0-41a28bb21ed5"}, {"url": "https://github.com/mlflow/mlflow/commit/f9b1eb510478570609ef451984a255775aa4b937"}], "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."}], "problemTypes": [{"descriptions": [{"lang": "en", "type": "CWE", "cweId": "CWE-284", "description": "CWE-284 Improper Access Control"}]}], "providerMetadata": {"orgId": "c09c270a-b464-47c1-9133-acb35b22c19a", "shortName": "@huntr_ai", "dateUpdated": "2026-07-02T07:32:58.308Z"}}}, "cveMetadata": {"cveId": "CVE-2026-8147", "state": "PUBLISHED", "dateUpdated": "2026-07-02T12:28:31.554Z", "dateReserved": "2026-05-08T02:45:28.857Z", "assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a", "datePublished": "2026-07-02T07:32:58.308Z", "assignerShortName": "@huntr_ai"}, "dataVersion": "5.2"}

{}

{"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"}

{"affected": [{"configurations": [{"platform": null, "status": "affected", "versions": {"scheme": "semver", "value": "[0,3.14.0)"}}], "enrichment": {"confidence": 100.0, "confidence_source": "matching", "scores": [{"score": 100.0, "source": "matching"}]}, "original": {"product": "mlflow/mlflow", "source": "cna", "vendor": "mlflow"}, "product": "mlflow/mlflow", "vendor": "mlflow"}], "created": "2026-07-02T09:30:05.655789+00:00", "updated": "2026-07-08T01:00:04.626070+00:00", "vendors": ["mlflow", "mlflow$PRODUCT$mlflow/mlflow"]}