CVE-2024-3099

MEDIUM

MLflow < 2.11.3 - Model Name Spoofing and Denial of Service via URL Encoding

Title source: llm
STIX 2.1

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.

References (1)

Core 1
Core References
Exploit, Issue Tracking, Third Party Advisory
https://huntr.com/bounties/8d96374a-ce8d-480e-9cb0-0a7e5165c24a

Scores

CVSS v3 5.4
EPSS 0.0006
EPSS Percentile 19.5%
Attack Vector NETWORK
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L

CISA SSVC

Vulnrichment
Exploitation poc
Automatable no
Technical Impact partial

Details

CWE
CWE-475
Status published
Products (2)
lfprojects/mlflow
pypi/mlflow 0 - 2.11.3PyPI
Published Jun 06, 2024
Tracked Since Feb 18, 2026