Remote file access vulnerability in mlflow server and mlflow ui CLIs

Exploitation

No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.

CVSS

not scored

EPSS

No dated EPSS signal available.

As published by the source; long descriptions are shortened.

Impact Users of the MLflow Open Source Project who are hosting the MLflow Model Registry using the mlflow server or mlflow ui commands using an MLflow version older than MLflow 2.3.1 may be vulnerable to a remote file access exploit if they are not limiting who can query their server (for example, by using a cloud VPC, an IP allowlist for inbound requests, or authentication / authorization middleware). This issue only affects users and integrations that run the mlflow server and mlflow ui commands. Integrations that do not make use of mlflow server or mlflow ui are unaffected; for example, the Databricks Managed MLflow product and MLflow on Azure Machine Learning do not make use of these commands and are not impacted by these vulnerabilities in any way. The vulnerability is very similar to https://nvd.nist.gov/vuln/detail/CVE-2023-1177, and a separate CVE will be published and updated here shortly. Patches This vulnerability has been patched in MLflow 2.3.1, which was released to…

Published by the source

1 May 2023, 13:43 UTC

Last modified by the source

28 Nov 2024, 05:40 UTC

Source last checked

26 Oct 2026, 13:11 UTC

1. Revision 2 · amended · 26 Oct 2026

   Amended from ghsa record GHSA-83fm-w79m-64r5

2. Revision 1 · created · 24 Oct 2026

   Published from osv record GHSA-83fm-w79m-64r5

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# Patch Next advisory brief: GHSA-83fm-w79m-64r5

Advisory: Remote file access vulnerability in `mlflow server` and `mlflow ui` CLIs
IDs: GHSA-83fm-w79m-64r5
Record: https://patchnext.com/advisories/ghsa-83fm-w79m-64r5 (revision 2, source checked 26 Oct 2026, 13:11 UTC)
Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected.
Severity: Unrated
Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV.
Vendor response: Vendor fix available; fixed versions by package: mlflow 2.3.1. A vendor fix does not mean a deployment is fixed.

## Affected components
- PyPI mlflow: affected < 2.3.1; fixed in 2.3.1

## Suggested inspection (read-only)
- `python -m pip show mlflow`: prints the installed version. Run with the environment that serves production active.

## Supported action
Upgrade each affected component to a fixed version on its release line. For a transitive dependency, upgrade the parent package or add an override or constraint, then regenerate the lockfile. Redeploy every environment that ran an affected version.

## Required regression checks
- Run the test suite and a production build.
- Exercise the features that depend on mlflow.
- Repeat the inspection and confirm that only fixed versions remain installed.

## Rollback considerations
- Keep the previous lockfile and deployment artifact. Rolling back reinstates the vulnerable version, so apply any documented mitigation while you fix forward.

## Unresolved questions
- Which deployments run an affected version?
- Exploitation status can change. Check again before lowering the priority.
- Mark the work resolved only after the fixed version is verified in production.

## Sources
- Verified: https://osv.dev/vulnerability/GHSA-83fm-w79m-64r5 (OSV record GHSA-83fm-w79m-64r5 lists affected ranges: PyPI mlflow >=0 <2.3.1 (fixed))
- Verified: https://github.com/advisories/GHSA-83fm-w79m-64r5 (GitHub-reviewed advisory GHSA-83fm-w79m-64r5 lists affected ranges: PyPI mlflow >=0 <2.3.1)

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