Vulnerability · Published Jun 6, 2024 · Assigned by @huntr_ai
CVE-2024-3099Denial of Service and Data Model Poisoning via URL Encoding in mlflow/mlflow
Medium 5.4
In plain English
A medium-severity security flaw in mlflow/mlflow from mlflow. Proof-of-concept exploit code is public. The chance it is exploited in the next 30 days is estimated at 0.4% (higher than 39% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official description
A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts.
Affected packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | mlflow | 2.11.3 | GHSA-8f8q-q2j7-7j2m |
| PyPI | mlflow | 2.11.3 | PYSEC-2026-1645 |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| mlflow | mlflow/mlflow | unspecified – through latest |
Weakness: CWE-475 · Vector: CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L