MLflow: Remote code execution on unauthenticated MLflow servers via third-party scorer deserialization importing caller-placed artifact modules
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
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| mlflow | mlflow | affected |
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| Mlflow | Mlflow |
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| Source | ID | Title |
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Github GHSA |
GHSA-26p8-2jq9-3vq9 | MLflow vulnerable to remote code execution on unauthenticated servers via third-party scorer deserialization importing caller-placed artifact modules |
No CVSS v4.0
No CVSS v3.0
No CVSS v2
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.704% probability within 30 days)
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ssvc
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| First Time appeared |
Mlflow
Mlflow mlflow |
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| Vendors & Products |
Mlflow
Mlflow mlflow |
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| Description | MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.12.0rc0 until 3.17.0, third-party scorer deserialization in mlflow/genai/scorers/base.py accepts request-selected descendants of THIRD_PARTY_SCORER_ALLOWED_MODULES rather than requiring an exact allowed module. A caller can use MLflow artifact endpoints to place a Python module beneath a writable allowed package and submit its module and class through /ajax-api/3.0/mlflow/scorer/invoke. Scorer.model_validate_json() imports the module and constructs the class before trace processing. Authentication-disabled deployments permit this code execution without credentials, while basic-auth deployments require a principal capable of creating an experiment and run and uploading artifacts. In either configuration, the allowed scorer package must be writable by the server process. This issue is fixed in version 3.17.0. | |
| Title | MLflow: Remote code execution on unauthenticated MLflow servers via third-party scorer deserialization importing caller-placed artifact modules | |
| Weaknesses | CWE-470 CWE-94 |
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| Metrics |
cvssV3_1
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