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THREATINT
PUBLISHED

CVE-2024-3099

Denial of Service and Data Model Poisoning via URL Encoding in mlflow/mlflow



Assigner@huntr_ai
Reserved2024-03-29
Published2024-06-06
Updated2024-08-01

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.



MEDIUM: 5.4CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L

Product status

Any version
affected

References

https://huntr.com/bounties/8d96374a-ce8d-480e-9cb0-0a7e5165c24a

cve.org CVE-2024-3099

nvd.nist.gov CVE-2024-3099

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