CVE-2025-1474: Mlflow MLflow Has Weak Password Requirements Vulnerability

LOW
Advisory Identifier: GHSA-4rj2-9gcx-5qhx
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CVSS 3.8
CWE-521
Published
Advisory Summary

CVE-2025-1474 is a LOW (CVSS 3.8) mlflow has weak password requirements vulnerability (CWE-521: Weak Password Requirements) affecting Mlflow libraries in the PyPI ecosystem. The issue involves mlflow has weak password requirements. Remediation is available by upgrading affected packages to version 2.19.0.

CVE-2025-1474 at a Glance

CVE Identifier CVE-2025-1474
GHSA Identifier GHSA-4rj2-9gcx-5qhx
Severity LOW
CVSS v3.1 Base Score 3.8
CWE Classification CWE-521: Weak Password Requirements
Affected Product Mlflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 3.8

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.0/AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:N).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required High (PR:H)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality Low (C:L)
Integrity Low (I:L)
Availability None (A:N)

How to Fix CVE-2025-1474

To remediate this vulnerability, upgrade all affected Mlflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

mlflow fixed: 2.19.0 
pip install mlflow>=2.19.0
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show mlflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2025-1474, inspect your installed packages using pip:

pip show mlflow

Analyze the terminal output to locate any version of Mlflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 2.19.0), your application is affected.

Note: The pip show mlflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-521: Weak Password Requirements, where the product does not require that users should have strong passwords. In Mlflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

In mlflow/mlflow version 2.18, an admin is able to create a new user account without setting a password. This vulnerability could lead to security risks, as accounts without passwords may be susceptible to unauthorized access. Additionally, this issue violates best practices for secure user account management. The issue is fixed in version 2.19.0.

CVE-2025-1474 Affected Mlflow Versions

1 component(s)
Fixed Versions:
2.19.0
Product / Package Ecosystem Affected Versions Fixed Version
mlflow
pypi/mlflow
PyPI
< 2.19.0
2.19.0

References

NVD — CVE-2025-1474 NVD
https://nvd.nist.gov/vuln/detail/CVE-2025-1474
Security Fix Commit FIX COMMIT
https://github.com/mlflow/mlflow/commit/149c9e18aa219bc47e86b432e130e467a36f4a17
Mlflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow
Mlflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2025-17.yaml
huntr.com/bounties/e79f7774-1... WEB
https://huntr.com/bounties/e79f7774-10fe-46b2-b522-e73b748e3b2d

Frequently Asked Questions

What is CVE-2025-1474?
CVE-2025-1474 is a security vulnerability in Mlflow involving MLflow has Weak Password Requirements under CWE-521: Weak Password Requirements.
Which Mlflow versions are affected?
Affected versions include releases prior to 2.19.0 across affected packages: mlflow.
What version fixes CVE-2025-1474?
Upgrading to 2.19.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is mlflow affected?
Yes, mlflow is affected in releases prior to 2.19.0. Upgrade your dependency to 2.19.0 or later.
What is the CVSS score of CVE-2025-1474?
CVE-2025-1474 has a CVSS v3.1 base score of 3.8 (LOW) with vector string CVSS:3.0/AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:N.
What CWE is associated with CVE-2025-1474?
CVE-2025-1474 is classified under CWE-521: Weak Password Requirements (The product does not require that users should have strong passwords.).
How can I check PyPI dependencies for CVE-2025-1474?
Run the dependency tree command: 'pip show mlflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-4rj2-9gcx-5qhx",
  "modified" : "2025-04-09T20:06:06Z",
  "published" : "2025-03-20T12:32:53Z",
  "aliases" : [ "CVE-2025-1474" ],
  "summary" : "MLflow has Weak Password Requirements",
  "details" : "In mlflow/mlflow version 2.18, an admin is able to create a new user account without setting a password. This vulnerability could lead to security risks, as accounts without passwords may be susceptible to unauthorized access. Additionally, this issue violates best practices for secure user account management. The issue is fixed in version 2.19.0.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.0/AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:N"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "mlflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "2.19.0"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2025-1474"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/commit/149c9e18aa219bc47e86b432e130e467a36f4a17"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/mlflow/mlflow"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2025-17.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://huntr.com/bounties/e79f7774-10fe-46b2-b522-e73b748e3b2d"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-521" ],
    "severity" : "LOW",
    "github_reviewed" : true,
    "github_reviewed_at" : "2025-03-21T23:36:26Z",
    "nvd_published_at" : "2025-03-20T10:15:54Z"
  }
}