{"api_version":"1","generated_at":"2026-10-24T00:30:33+00:00","cve":"CVE-2026-115886","urls":{"html":"https://cve.report/CVE-2026-115886","api":"https://cve.report/api/cve/CVE-2026-115886.json","docs":"https://cve.report/api","cve_org":"https://www.cve.org/CVERecord?id=CVE-2026-115886","nvd":"https://nvd.nist.gov/vuln/detail/CVE-2026-115886"},"summary":{"title":"MLflow: SSRF on unauthenticated MLflow servers via third-party scorer kwargs in the scorer invoke, register, and GenAI evaluate endpoints","description":"MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.12.0rc0 until 3.17.0, the scorer invoke, register, and GenAI evaluate endpoints, including unauthenticated POST /ajax-api/3.0/mlflow/scorer/invoke, accept serialized third-party scorer data that Scorer.model_validate_json resolves using a module-path allowlist without constraining the selected class or its constructor arguments. When optional trulens and trulens-providers-litellm packages are installed, an attacker can select mlflow.genai.scorers.trulens, choose a model URI outside MLflow's native provider registry so execution uses the LiteLLM fallback, and supply api_base and api_key values that cause the server to send an outbound request to an attacker-chosen or internal host with attacker-controlled headers and body. The vulnerable deserialization occurs before a tracking-store lookup or job submission. This issue is fixed in version 3.17.0.","state":"PUBLISHED","assigner":"GitHub_M","published_at":"2026-10-23 22:16:58","updated_at":"2026-10-23 22:16:58"},"problem_types":["CWE-470","CWE-918","CWE-470 CWE-470: Use of Externally-Controlled Input to Select Classes or Code ('Unsafe Reflection')","CWE-918 CWE-918: Server-Side Request Forgery (SSRF)"],"metrics":[{"version":"3.1","source":"security-advisories@github.com","type":"Secondary","score":"6.5","severity":"MEDIUM","vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N","data":{"version":"3.1","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N","baseScore":6.5,"baseSeverity":"MEDIUM","attackVector":"NETWORK","attackComplexity":"LOW","privilegesRequired":"NONE","userInteraction":"NONE","scope":"UNCHANGED","confidentialityImpact":"LOW","integrityImpact":"LOW","availabilityImpact":"NONE"}},{"version":"3.1","source":"CNA","type":"DECLARED","score":"6.5","severity":"MEDIUM","vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N","data":{"attackComplexity":"LOW","attackVector":"NETWORK","availabilityImpact":"NONE","baseScore":6.5,"baseSeverity":"MEDIUM","confidentialityImpact":"LOW","integrityImpact":"LOW","privilegesRequired":"NONE","scope":"UNCHANGED","userInteraction":"NONE","vectorString":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N","version":"3.1"}}],"references":[{"url":"https://github.com/mlflow/mlflow/security/advisories/GHSA-2wqp-q3c6-ccj5","name":"https://github.com/mlflow/mlflow/security/advisories/GHSA-2wqp-q3c6-ccj5","refsource":"security-advisories@github.com","tags":[],"title":"","mime":"","httpstatus":"","archivestatus":"0"},{"url":"https://github.com/mlflow/mlflow/pull/25890","name":"https://github.com/mlflow/mlflow/pull/25890","refsource":"security-advisories@github.com","tags":[],"title":"","mime":"","httpstatus":"","archivestatus":"0"},{"url":"https://github.com/mlflow/mlflow/commit/bac30b4148c4f40045b4d4db07ae60ab3838803f","name":"https://github.com/mlflow/mlflow/commit/bac30b4148c4f40045b4d4db07ae60ab3838803f","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-2026-115886","name":"CVE Program record","refsource":"CVE.ORG","tags":["canonical"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2026-115886","name":"NVD vulnerability detail","refsource":"NVD","tags":["canonical","analysis"]}],"affected":[{"source":"CNA","vendor":"mlflow","product":"mlflow","version":"affected >= 3.12.0rc0, < 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":">= 3.12.0rc0, < 3.17.0"}]}],"descriptions":[{"lang":"en","value":"MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. 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From 3.12.0rc0 until 3.17.0, the scorer invoke, register, and GenAI evaluate endpoints, including unauthenticated POST /ajax-api/3.0/mlflow/scorer/invoke, accept serialized third-party scorer data that Scorer.model_validate_json resolves using a module-path allowlist without constraining the selected class or its constructor arguments. When optional trulens and trulens-providers-litellm packages are installed, an attacker can select mlflow.genai.scorers.trulens, choose a model URI outside MLflow's native provider registry so execution uses the LiteLLM fallback, and supply api_base and api_key values that cause the server to send an outbound request to an attacker-chosen or internal host with attacker-controlled headers and body. The vulnerable deserialization occurs before a tracking-store lookup or job submission. This issue is fixed in version 3.17.0.","Type":"Description","Title":"MLflow: SSRF on unauthenticated MLflow servers via third-party s"}]}}}