CVE-2026-69148

GHSA-gqch-g4w5-7qcw HIGH
Published August 17, 2026

MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, CreateModelVersion accepts a run_id or model_id after _validate_source_run() or _validate_source_model() in mlflow/server/handlers.py verifies only path containment,...

Full CISO analysis pending enrichment.

What systems are affected?

Package Ecosystem Vulnerable Range Patched
MLflow npm < 3.15.0 3.15.0
27.5K OpenSSF 5.6 683 dependents Pushed yesterday 36% patched ~70d to patch Full package profile →

Do you use MLflow? You're affected.

How severe is it?

CVSS 3.1
7.1 / 10
EPSS
N/A
Exploitation Status
No known exploitation
Sophistication
N/A

What is the attack surface?

AV AC PR UI S C I A
AV Network
AC Low
PR Low
UI None
S Unchanged
C High
I Low
A None

What should I do?

Patch available

Update MLflow to version 3.15.0

Which compliance frameworks are affected?

Compliance analysis pending. Sign in for full compliance mapping when available.

Frequently Asked Questions

What is CVE-2026-69148?

MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, CreateModelVersion accepts a run_id or model_id after _validate_source_run() or _validate_source_model() in mlflow/server/handlers.py verifies only path containment, allowing authenticated users to create a model version that references another user's artifact directory and read files through GET /model-versions/get-artifact without the required READ permission. This issue is fixed in version 3.15.0.

Is CVE-2026-69148 actively exploited?

No confirmed active exploitation of CVE-2026-69148 has been reported, but organizations should still patch proactively.

How to fix CVE-2026-69148?

Update to patched version: MLflow 3.15.0.

What is the CVSS score for CVE-2026-69148?

CVE-2026-69148 has a CVSS v3.1 base score of 7.1 (HIGH).

What are the technical details?

Original Advisory

MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, CreateModelVersion accepts a run_id or model_id after _validate_source_run() or _validate_source_model() in mlflow/server/handlers.py verifies only path containment, allowing authenticated users to create a model version that references another user's artifact directory and read files through GET /model-versions/get-artifact without the required READ permission. This issue is fixed in version 3.15.0.

Weaknesses (CWE)

CWE-862 — Missing Authorization: The product does not perform an authorization check when an actor attempts to access a resource or perform an action.

  • [Architecture and Design] Divide the product into anonymous, normal, privileged, and administrative areas. Reduce the attack surface by carefully mapping roles with data and functionality. Use role-based access control (RBAC) [REF-229] to enforce the roles at the appropriate boundaries. Note that this approach may not protect against horizontal authorization, i.e., it will not protect a user from attacking others with the same role.
  • [Architecture and Design] Ensure that access control checks are performed related to the business logic. These checks may be different than the access control checks that are applied to more generic resources such as files, connections, processes, memory, and database records. For example, a database may restrict access for medical records to a specific database user, but each record might only be intended to be accessible to the patient and the patient's doctor [REF-7].

Source: MITRE CWE corpus.

CVSS Vector

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N

Timeline

Published
August 17, 2026
Last Modified
August 17, 2026
First Seen
August 18, 2026

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