# CVE-2026-2734: MLflow improper access control in SearchModelVersions API

Source: https://junglewise.ai/threats/cve-2026-2734-mlflow-improper-access-control-in-searchmodelversions-api  
Publisher: Junglewise Threat Intelligence, https://junglewise.ai/threats  
Published: 2026-05-21. Updated: 2026-06-12  
License: CC BY 4.0 with a link back

CVE-2026-2734 · Severity: medium · CVSS 6.5 · Published 2026-05-21

MLflow, a platform for managing the machine learning lifecycle, contains a vulnerability where users with basic login access can view information about all registered machine learning models. This allows unauthorized users to see sensitive metadata, including model names, descriptions, and source locations, which could expose proprietary intellectual property in shared or multi-tenant environments. The issue is fixed in version 3.10.0.

Technologies: [mlflow (PyPI)](https://junglewise.ai/threats/technologies/mlflow). Vendors: [PyPI](https://junglewise.ai/threats/vendors/pypi).

## Quick answers

**Is CVE-2026-2734 exploited in the wild?** No. Junglewise Threat Intelligence has no report of CVE-2026-2734 being exploited in the wild.

**How severe is CVE-2026-2734?** Medium severity, with a CVSS score of 6.5, published 21 May 2026.

**Which products and versions are affected?** mlflow (PyPI) < 3.10.0, ECOSYSTEM:introduced=0,fixed=3.10.0.

**Is there a fix for CVE-2026-2734?** Yes. mlflow (PyPI): upgrade to 3.10.0 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.

**How is CVE-2026-2734 attacked?** It is attacked over the network, in a software library.

**Am I affected by CVE-2026-2734?** Check whether you run mlflow (PyPI) at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

## How to fix

- mlflow (PyPI): upgrade to 3.10.0 or later

  ```sh
  pip install "mlflow>=3.10.0"
  ```


## Technical details

An improper access control vulnerability (CWE-284) exists in MLflow versions up to 3.9.0. The `SearchModelVersions` REST API endpoint and the `mlflowSearchModelVersions` GraphQL query fail to implement per-model authorization checks when basic authentication is enabled. This occurs because the endpoint was omitted from the `BEFORE_REQUEST_VALIDATORS` and `AFTER_REQUEST_HANDLERS` for REST, and from `GraphQLAuthorizationMiddleware.PROTECTED_FIELDS` for GraphQL. An authenticated attacker can exploit this to enumerate all model versions, tags, and source URIs across the entire registry. The vulnerability is resolved in version 3.10.0 by enforcing parent model permission filtering.

## Affected products

- mlflow mlflow < 3.10.0

## Identifiers

- CVE-2026-2734
- GHSA-w5xq-c4pf-ghq7
- PYSEC-2026-2660

## Timeline

- 2026-02-19: patched: Fix committed to repository
- 2026-05-21: disclosed: Vulnerability disclosed via huntr.dev and GHSA
- 2026-05-21: advisory: GitHub Advisory published

## References

- [https://github.com/mlflow/mlflow/commit/6989066af33fdcb03588fd71a1a67f8fc5ef12c9](https://github.com/mlflow/mlflow/commit/6989066af33fdcb03588fd71a1a67f8fc5ef12c9)
- [https://huntr.com/bounties/d632f783-b2c7-4a3b-af5e-1d693e841c08](https://huntr.com/bounties/d632f783-b2c7-4a3b-af5e-1d693e841c08)

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- [MLflow arbitrary code execution in third-party scorer deserialization](https://junglewise.ai/threats/cve-2026-116692-mlflow-is-an-open-source-ai-engineering-platform-for-agents)
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- [MLflow path traversal in prompt model version artifact access](https://junglewise.ai/threats/cve-2026-116690-mlflow-is-an-open-source-ai-engineering-platform-for-agents)
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