CVE-2024-27134: Mlflow MLflow's Excessive Directory Permissions Allow Vulnerability

HIGH
Advisory Identifier: GHSA-qpgc-w4mg-6v92
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CVSS 7.0
CWE-276
Published
Advisory Summary

CVE-2024-27134 is a HIGH (CVSS 7.0) mlflow's excessive directory permissions allow vulnerability (CWE-276: Incorrect Default Permissions) affecting Mlflow libraries in the PyPI ecosystem. The issue involves mlflow's excessive directory permissions allow local privilege escalation. Remediation is available by upgrading affected packages to version 2.16.0.

CVE-2024-27134 at a Glance

CVE Identifier CVE-2024-27134
GHSA Identifier GHSA-qpgc-w4mg-6v92
Severity HIGH
CVSS v3.1 Base Score 7.0
CWE Classification CWE-276: Incorrect Default Permissions
Affected Product Mlflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 7.0

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H).

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

How to Fix CVE-2024-27134

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: 2.16.0 
pip install mlflow>=2.16.0
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-2024-27134, 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 2.16.0), 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-276: Incorrect Default Permissions, where during installation, installed file permissions are set to allow anyone to modify those files. 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

Excessive directory permissions in MLflow leads to local privilege escalation when using spark_udf. This behavior can be exploited by a local attacker to gain elevated permissions by using a ToCToU attack. The issue is only relevant when the spark_udf() MLflow API is called.

CVE-2024-27134 Affected Mlflow Versions

1 component(s)
Fixed Versions:
2.16.0
Product / Package Ecosystem Affected Versions Fixed Version
mlflow
pypi/mlflow
PyPI
< 2.16.0
2.16.0

References

NVD — CVE-2024-27134 NVD
https://nvd.nist.gov/vuln/detail/CVE-2024-27134
Mlflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow/pull/10874
Security Fix Commit FIX COMMIT
https://github.com/mlflow/mlflow/commit/0b1d995d66a678153e01ed3040f3f4dfc16a0d6b
Mlflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow

Frequently Asked Questions

What is CVE-2024-27134?
CVE-2024-27134 is a security vulnerability in Mlflow involving MLflow's excessive directory permissions allow local privilege escalation under CWE-276: Incorrect Default Permissions.
Which Mlflow versions are affected?
Affected versions include releases prior to 2.16.0 across affected packages: mlflow.
What version fixes CVE-2024-27134?
Upgrading to 2.16.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is mlflow affected?
Yes, mlflow is affected in releases prior to 2.16.0. Upgrade your dependency to 2.16.0 or later.
What is the CVSS score of CVE-2024-27134?
CVE-2024-27134 has a CVSS v3.1 base score of 7.0 (HIGH) with vector string CVSS:3.1/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2024-27134?
CVE-2024-27134 is classified under CWE-276: Incorrect Default Permissions (During installation, installed file permissions are set to allow anyone to modify those files.).
How can I check PyPI dependencies for CVE-2024-27134?
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-qpgc-w4mg-6v92",
  "modified" : "2024-11-25T19:41:56Z",
  "published" : "2024-11-25T18:33:26Z",
  "aliases" : [ "CVE-2024-27134" ],
  "summary" : "MLflow's excessive directory permissions allow local privilege escalation",
  "details" : "Excessive directory permissions in MLflow leads to local privilege escalation when using spark_udf. This behavior can be exploited by a local attacker to gain elevated permissions by using a ToCToU attack. The issue is only relevant when the spark_udf() MLflow API is called.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H"
  }, {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:L/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "mlflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "2.16.0"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2024-27134"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/pull/10874"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/commit/0b1d995d66a678153e01ed3040f3f4dfc16a0d6b"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/mlflow/mlflow"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-276" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2024-11-25T19:41:56Z",
    "nvd_published_at" : "2024-11-25T14:15:06Z"
  }
}