EUVD-2026-39984
GHSA-wfp4-8wh2-c48v
Severity by source
CVSS:4.0/AV:N/AC:H/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
Network-accessible API requires low-privilege authentication and high complexity; no scope change and all impacts limited to label schema metadata only.
Primary rating from Vendor (VulDB).
CVSS VectorVendor: VulDB
Lifecycle Timeline
2DescriptionCVE.org
A vulnerability has been found in MLflow up to 4666cffc7912ea606d592fc38d6a75e2935f65e7. The impacted element is an unknown function of the component Experiment-scoped Label Schema CRUD API. Such manipulation leads to missing authorization. It is possible to launch the attack remotely. A high complexity level is associated with this attack. The exploitability is regarded as difficult. The exploit has been disclosed to the public and may be used. A reply to the GitHub issue explains, that "[t]he labeling schema PR has not been merged yet. The auth handlers will be added before the release."
AnalysisAI
Missing authorization in MLflow's Experiment-scoped Label Schema CRUD API allows a remote, low-privileged attacker to perform unauthorized read, create, update, or delete operations on label schema resources. The vulnerability stems from a pre-release feature that was disclosed before its authentication handlers were implemented - a GitHub maintainer confirmed: 'The auth handlers will be added before the release.' A proof-of-concept is publicly available via the referenced GitHub issue. Despite network accessibility, the CVSS 4.0 score of 1.3 reflects high attack complexity and limited impact scope, and no CISA KEV listing has been issued.
Technical ContextAI
MLflow is an open-source platform widely used in data science and MLOps workflows for experiment tracking, model registry, and deployment. The affected component is the Experiment-scoped Label Schema CRUD API, a feature managing label schemas tied to individual MLflow experiments. CWE-862 (Missing Authorization) describes the root cause: the API endpoints perform no authorization checks, meaning any authenticated user can invoke privileged CRUD operations regardless of their intended access level. Per the GitHub thread, this feature exists in an unmerged pull request - the code up to commit 4666cffc7912ea606d592fc38d6a75e2935f65e7 contains the API surface but not the corresponding auth handlers. CPE cpe:2.3:a:n/a:mlflow:*:*:*:*:*:*:*:* covers the affected range with no specific version bound yet assigned.
RemediationAI
No vendor-released patch has been confirmed at time of analysis - the GitHub maintainer response indicates auth handlers will be added prior to the feature's official release, meaning the fix is planned but not yet in a tagged version. Organizations running development or pre-release MLflow builds containing the label schema feature should restrict network access to the MLflow tracking server to trusted, authorized users only, as a compensating control; this reduces the attack surface but does not eliminate the missing authorization flaw. Alternatively, avoid deploying MLflow builds from the affected commit range in shared or multi-tenant environments until a patched release is available. Monitor the GitHub issue at https://github.com/mlflow/mlflow/issues/23608 and the MLflow changelog for a formal patch release. Production deployments using stable MLflow releases are likely not affected and require no immediate action.
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Same weakness CWE-862 – Missing Authorization
View allSame technique Authentication Bypass
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External POC / Exploit Code
Leaving vuln.today