{"api_version":"1","generated_at":"2026-10-28T00:22:45+00:00","cve":"CVE-2026-116690","urls":{"html":"https://cve.report/CVE-2026-116690","api":"https://cve.report/api/cve/CVE-2026-116690.json","docs":"https://cve.report/api","cve_org":"https://www.cve.org/CVERecord?id=CVE-2026-116690","nvd":"https://nvd.nist.gov/vuln/detail/CVE-2026-116690"},"summary":{"title":"MLflow: Arbitrary file read on unauthenticated MLflow servers via prompt model version source","description":"MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.10.0 until 3.17.0, the prompt branch in _create_model_version() accepts schemeless relative sources because path validation runs only when a source has a URL scheme, and mlflow.prompt.is_prompt is interpreted by tag presence rather than a true value. A remote caller can store a server-local path as the model version artifact location and use /api/2.0/mlflow/model-versions/get-artifact to read files accessible to the MLflow server process. Default unauthenticated servers require no privileges, while basic-auth deployments are exposed to authenticated users who can create registered models. This issue is fixed in version 3.17.0.","state":"PUBLISHED","assigner":"GitHub_M","published_at":"2026-10-27 20:17:14","updated_at":"2026-10-27 20:17:14"},"problem_types":["CWE-22","CWE-22 CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')"],"metrics":[{"version":"3.1","source":"security-advisories@github.com","type":"Secondary","score":"7.5","severity":"HIGH","vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N","data":{"version":"3.1","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N","baseScore":7.5,"baseSeverity":"HIGH","attackVector":"NETWORK","attackComplexity":"LOW","privilegesRequired":"NONE","userInteraction":"NONE","scope":"UNCHANGED","confidentialityImpact":"HIGH","integrityImpact":"NONE","availabilityImpact":"NONE"}},{"version":"3.1","source":"CNA","type":"DECLARED","score":"7.5","severity":"HIGH","vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N","data":{"attackComplexity":"LOW","attackVector":"NETWORK","availabilityImpact":"NONE","baseScore":7.5,"baseSeverity":"HIGH","confidentialityImpact":"HIGH","integrityImpact":"NONE","privilegesRequired":"NONE","scope":"UNCHANGED","userInteraction":"NONE","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N","version":"3.1"}}],"references":[{"url":"https://github.com/mlflow/mlflow/security/advisories/GHSA-m65p-9j7q-6w33","name":"https://github.com/mlflow/mlflow/security/advisories/GHSA-m65p-9j7q-6w33","refsource":"security-advisories@github.com","tags":[],"title":"","mime":"","httpstatus":"","archivestatus":"0"},{"url":"https://github.com/mlflow/mlflow/commit/81730a2ce4ebcd60d5d18f68c96f422ad7e30772","name":"https://github.com/mlflow/mlflow/commit/81730a2ce4ebcd60d5d18f68c96f422ad7e30772","refsource":"security-advisories@github.com","tags":[],"title":"","mime":"","httpstatus":"","archivestatus":"0"},{"url":"https://github.com/mlflow/mlflow/pull/25870","name":"https://github.com/mlflow/mlflow/pull/25870","refsource":"security-advisories@github.com","tags":[],"title":"","mime":"","httpstatus":"","archivestatus":"0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.17.0","name":"https://github.com/mlflow/mlflow/releases/tag/v3.17.0","refsource":"security-advisories@github.com","tags":[],"title":"","mime":"","httpstatus":"","archivestatus":"0"},{"url":"https://www.cve.org/CVERecord?id=CVE-2026-116690","name":"CVE Program record","refsource":"CVE.ORG","tags":["canonical"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2026-116690","name":"NVD vulnerability detail","refsource":"NVD","tags":["canonical","analysis"]}],"affected":[{"source":"CNA","vendor":"mlflow","product":"mlflow","version":"affected >= 3.10.0, < 3.17.0","platforms":[]}],"timeline":[],"solutions":[],"workarounds":[],"exploits":[],"credits":[],"nvd_cpes":[],"vendor_comments":[],"enrichments":{"kev":null,"epss":null,"legacy_qids":[]},"source_records":{"cve_program":{"containers":{"cna":{"affected":[{"product":"mlflow","vendor":"mlflow","versions":[{"status":"affected","version":">= 3.10.0, < 3.17.0"}]}],"descriptions":[{"lang":"en","value":"MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.10.0 until 3.17.0, the prompt branch in _create_model_version() accepts schemeless relative sources because path validation runs only when a source has a URL scheme, and mlflow.prompt.is_prompt is interpreted by tag presence rather than a true value. A remote caller can store a server-local path as the model version artifact location and use /api/2.0/mlflow/model-versions/get-artifact to read files accessible to the MLflow server process. Default unauthenticated servers require no privileges, while basic-auth deployments are exposed to authenticated users who can create registered models. This issue is fixed in version 3.17.0."}],"metrics":[{"cvssV3_1":{"attackComplexity":"LOW","attackVector":"NETWORK","availabilityImpact":"NONE","baseScore":7.5,"baseSeverity":"HIGH","confidentialityImpact":"HIGH","integrityImpact":"NONE","privilegesRequired":"NONE","scope":"UNCHANGED","userInteraction":"NONE","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N","version":"3.1"}}],"problemTypes":[{"descriptions":[{"cweId":"CWE-22","description":"CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')","lang":"en","type":"CWE"}]}],"providerMetadata":{"dateUpdated":"2026-10-27T19:42:35.798Z","orgId":"a0819718-46f1-4df5-94e2-005712e83aaa","shortName":"GitHub_M"},"references":[{"name":"https://github.com/mlflow/mlflow/security/advisories/GHSA-m65p-9j7q-6w33","tags":["x_refsource_CONFIRM"],"url":"https://github.com/mlflow/mlflow/security/advisories/GHSA-m65p-9j7q-6w33"},{"name":"https://github.com/mlflow/mlflow/pull/25870","tags":["x_refsource_MISC"],"url":"https://github.com/mlflow/mlflow/pull/25870"},{"name":"https://github.com/mlflow/mlflow/commit/81730a2ce4ebcd60d5d18f68c96f422ad7e30772","tags":["x_refsource_MISC"],"url":"https://github.com/mlflow/mlflow/commit/81730a2ce4ebcd60d5d18f68c96f422ad7e30772"},{"name":"https://github.com/mlflow/mlflow/releases/tag/v3.17.0","tags":["x_refsource_MISC"],"url":"https://github.com/mlflow/mlflow/releases/tag/v3.17.0"}],"source":{"advisory":"GHSA-m65p-9j7q-6w33","discovery":"UNKNOWN"},"title":"MLflow: Arbitrary file read on unauthenticated MLflow servers via prompt model version source"}},"cveMetadata":{"assignerOrgId":"a0819718-46f1-4df5-94e2-005712e83aaa","assignerShortName":"GitHub_M","cveId":"CVE-2026-116690","datePublished":"2026-10-27T19:42:35.798Z","dateReserved":"2026-10-26T20:00:59.830Z","dateUpdated":"2026-10-27T19:42:35.798Z","state":"PUBLISHED"},"dataType":"CVE_RECORD","dataVersion":"5.2"},"nvd":{"publishedDate":"2026-10-27 20:17:14","lastModifiedDate":"2026-10-27 20:17:14","problem_types":["CWE-22","CWE-22 CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')"],"metrics":{"cvssMetricV31":[{"source":"security-advisories@github.com","type":"Secondary","cvssData":{"version":"3.1","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N","baseScore":7.5,"baseSeverity":"HIGH","attackVector":"NETWORK","attackComplexity":"LOW","privilegesRequired":"NONE","userInteraction":"NONE","scope":"UNCHANGED","confidentialityImpact":"HIGH","integrityImpact":"NONE","availabilityImpact":"NONE"},"exploitabilityScore":3.9,"impactScore":3.6}]},"configurations":[]},"legacy_mitre":{"record":{"CveYear":"2026","CveId":"116690","Ordinal":"1","Title":"MLflow: Arbitrary file read on unauthenticated MLflow servers vi","CVE":"CVE-2026-116690","Year":"2026"},"notes":[{"CveYear":"2026","CveId":"116690","Ordinal":"1","NoteData":"MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.10.0 until 3.17.0, the prompt branch in _create_model_version() accepts schemeless relative sources because path validation runs only when a source has a URL scheme, and mlflow.prompt.is_prompt is interpreted by tag presence rather than a true value. A remote caller can store a server-local path as the model version artifact location and use /api/2.0/mlflow/model-versions/get-artifact to read files accessible to the MLflow server process. Default unauthenticated servers require no privileges, while basic-auth deployments are exposed to authenticated users who can create registered models. This issue is fixed in version 3.17.0.","Type":"Description","Title":"MLflow: Arbitrary file read on unauthenticated MLflow servers vi"}]}}}