Code execution via ungated DSPy pickle loading
Published Sep 23, 2026 · Updated Sep 23, 2026
Unsafe deserialization in MLflow 2.0 and later allows remote attackers to execute code when a crafted DSPy model artifact is loaded. In mlflow/dspy/load.py, the non-.pkl branch calls dspy.load with allow_pickle enabled without applying the disabled-deserialization control. The attacker must place the artifact in a model source, and code runs when an operator or application loads it while MLFLOW_ALLOW_PICKLE_DESERIALIZATION is false.
Summary
What happened
Unsafe deserialization in MLflow 2.0 and later allows remote attackers to execute code when a crafted DSPy model artifact is loaded. In mlflow/dspy/load.py, the non-.pkl branch calls dspy.load with allow_pickle enabled without applying the disabled-deserialization control. The attacker must place the artifact in a model source, and code runs when an operator or application loads it while MLFLOW_ALLOW_PICKLE_DESERIALIZATION is false.
The record
- CVE
- CVE-2026-96775
- Published
- Sep 23, 2026
- Updated
- Sep 23, 2026
- Vendor
- MLflow Project
- Product
- MLflow
- Classifications
- T1204.002
- Attack vector
- network
- Privileges
- Unavailable
Timeline
How it unfolded
- Sep 23, 2026CVE publishedPublication date reported by the CVE source.
- Sep 23, 2026Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
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- Affected versionversion=2.0
What conditions does exploitation require?
What is affected?
Published CVSS scores
No CVSS assessment is available in this record.
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Attacks
What attackers are doing with it
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Activity data is delayed. The latest report is Sep 28, 2026.
Weakness, pattern, technique
Public exploit references
- MLflow DSPy Pickle Deserialization Bypass PoCfunctional · demonstrated
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Technologies
Your stack
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Your stack
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