Undefined Behavior in mlflow
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 software
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| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | mlflow | < 2.11.3 | 2.11.3 |
References
- CVSS vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L- Weakness (CWE)
CWE-475- Platform
- Python (PyPI)
- Package
mlflow- Disclosed
- 06.06.2024
- Updated
- 11.10.2026 13:18
Sources and licenses
OSV / GitHub Advisory Database - GHSA-8f8q-q2j7-7j2m - CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-1645 - PyPA Advisory Database; CC BY 4.0
Vulnerability history: mlflow
All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.
- Total entries
- 82
- First → latest
- 02.2022 09.2026
- Without a fix
- 18
- Exploited in attacks
- 1
Severity breakdown
- Critical 20
- High 48
- Medium 13
- Low 1
Disclosures per year
- 2022: 1
- 2023: 22
- 2024: 24
- 2025: 8
- 2026: 27
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Undefined Behavior in mlflow this entry
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