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CVE-2024-3099

MEDIUM
Published 2024-06-06T18:08:16.402Z
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CVSS Score

V3.0
5.4
/10
CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L
Base Score Metrics
Exploitability: N/A Impact: N/A

EPSS Score

v2025.03.14
0.002
probability
of exploitation in the wild

There is a 0.2% chance that this vulnerability will be exploited in the wild within the next 30 days.

Updated: 2025-06-25
Exploit Probability
Percentile: 0.405
Higher than 40.5% of all CVEs

Attack Vector Metrics

Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED

Impact Metrics

Confidentiality
NONE
Integrity
LOW
Availability
LOW

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.

Available Exploits

No exploits available for this CVE.

Related News

No news articles found for this CVE.

Affected Products

GitHub Security Advisories

Community-driven vulnerability intelligence from GitHub

✓ GitHub Reviewed MODERATE

Undefined Behavior in mlflow

GHSA-8f8q-q2j7-7j2m

Advisory Details

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

PyPI mlflow
ECOSYSTEM: ≥0 <2.11.3

CVSS Scoring

CVSS Score

5.0

CVSS Vector

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

Advisory provided by GitHub Security Advisory Database. Published: June 6, 2024, Modified: October 11, 2024

References

Published: 2024-06-06T18:08:16.402Z
Last Modified: 2024-08-01T19:32:42.675Z
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