CVE-2026-4035: MLflow Environment Variable Injection Vulnerability

CRITICAL
Advisory Identifier: GHSA-g35p-px32-whv6
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CVSS 9.1
CWE-201
Published
Advisory Summary

CVE-2026-4035 is a CRITICAL (CVSS 9.1) environment variable injection vulnerability (CWE-201: Insertion of Sensitive Information Into Sent Data) affecting MLflow libraries in the PyPI ecosystem. The issue involves environment variable injection in ai gateway secrets enables server-side credential exfiltration. Remediation is available by upgrading affected packages to version 3.11.0.

CVE-2026-4035 at a Glance

CVE Identifier CVE-2026-4035
GHSA Identifier GHSA-g35p-px32-whv6
Severity CRITICAL
CVSS v3.1 Base Score 9.1
CWE Classification CWE-201: Insertion of Sensitive Information Into Sent Data
Affected Product MLflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 9.1

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

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

How to Fix CVE-2026-4035

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: 3.11.0 
pip install mlflow>=3.11.0
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-2026-4035, 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 3.11.0), 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-201: Insertion of Sensitive Information Into Sent Data, where the code transmits data to another actor, but a portion of the data includes sensitive information that should not be accessible to that actor. 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

A vulnerability in mlflow/mlflow versions prior to 3.11.0 allows for the resolution of environment variables in AI Gateway secrets, which can be exploited to exfiltrate sensitive server-side environment credentials to an attacker-controlled endpoint. This issue arises because the `api_key` field in gateway secrets can accept `$ENV_VAR` references, which are resolved against the MLflow server's environment during runtime. The resolved secrets are then sent in provider authentication headers to the configured upstream `api_base`. This vulnerability can be exploited by low-privileged authenticated users in basic-auth deployments or by unauthenticated users in default deployments without `basic-auth`. The impact includes potential leakage of sensitive credentials such as cloud artifact credentials (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`), which could lead to artifact poisoning and cross-boundary code execution in downstream environments. The issue is fixed in version 3.11.0.

CVE-2026-4035 Affected MLflow Versions

1 component(s)
Fixed Versions:
3.11.0
Product / Package Ecosystem Affected Versions Fixed Version
mlflow
pypi/mlflow
PyPI
< 3.11.0
3.11.0

References

NVD — CVE-2026-4035 NVD
https://nvd.nist.gov/vuln/detail/CVE-2026-4035
Security Fix Commit FIX COMMIT
https://github.com/mlflow/mlflow/commit/4a3f2f720cb4f058c9e0c5b883e0acc9ab64a7f3
MLflow Security Information SECURITY
https://access.redhat.com/security/cve/CVE-2026-4035
bugzilla.redhat.com/show_bug.cgi WEB
https://bugzilla.redhat.com/show_bug.cgi?id=2484318
MLflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow
huntr.com/bounties/f8e591a0-0... WEB
https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233
MLflow Security Information SECURITY
https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-4035.json

Frequently Asked Questions

What is CVE-2026-4035?
CVE-2026-4035 is a security vulnerability in MLflow involving Environment variable injection in AI Gateway secrets enables server-side credential exfiltration under CWE-201: Insertion of Sensitive Information Into Sent Data.
Which MLflow versions are affected?
Affected versions include releases prior to 3.11.0 across affected packages: mlflow.
What version fixes CVE-2026-4035?
Upgrading to 3.11.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is mlflow affected?
Yes, mlflow is affected in releases prior to 3.11.0. Upgrade your dependency to 3.11.0 or later.
What is the CVSS score of CVE-2026-4035?
CVE-2026-4035 has a CVSS v3.1 base score of 9.1 (CRITICAL) with vector string CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L.
What CWE is associated with CVE-2026-4035?
CVE-2026-4035 is classified under CWE-201: Insertion of Sensitive Information Into Sent Data (The code transmits data to another actor, but a portion of the data includes sensitive information that should not be accessible to that actor.).
How can I check PyPI dependencies for CVE-2026-4035?
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 
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  "published" : "2026-06-03T09:30:28Z",
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  "summary" : "MLflow: Environment variable injection in AI Gateway secrets enables server-side credential exfiltration",
  "details" : "A vulnerability in mlflow/mlflow versions prior to 3.11.0 allows for the resolution of environment variables in AI Gateway secrets, which can be exploited to exfiltrate sensitive server-side environment credentials to an attacker-controlled endpoint. This issue arises because the `api_key` field in gateway secrets can accept `$ENV_VAR` references, which are resolved against the MLflow server's environment during runtime. The resolved secrets are then sent in provider authentication headers to the configured upstream `api_base`. This vulnerability can be exploited by low-privileged authenticated users in basic-auth deployments or by unauthenticated users in default deployments without `basic-auth`. The impact includes potential leakage of sensitive credentials such as cloud artifact credentials (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`), which could lead to artifact poisoning and cross-boundary code execution in downstream environments. The issue is fixed in version 3.11.0.",
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}