CVE-2024-3099
Apache MLflow URL Encoding Model Nameenance Vulnerability
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.
INFO
Published Date :
June 6, 2024, 7:15 p.m.
Last Modified :
June 7, 2024, 2:56 p.m.
Source :
[email protected]
Remotely Exploitable :
Yes !
Impact Score :
2.5
Exploitability Score :
2.8
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2024-3099.
| URL | Resource |
|---|---|
| https://huntr.com/bounties/8d96374a-ce8d-480e-9cb0-0a7e5165c24a |
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2024-3099 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2024-3099 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
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CVE Received by [email protected]
Jun. 06, 2024
Action Type Old Value New Value Added 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. Added Reference huntr.dev https://huntr.com/bounties/8d96374a-ce8d-480e-9cb0-0a7e5165c24a [No types assigned] Added CWE huntr.dev CWE-475 Added CVSS V3 huntr.dev AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2024-3099 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2024-3099
weaknesses.