Arbitrary code execution via malicious PyTorch model
Published Jun 4, 2024 · Updated Aug 2, 2024
Unsafe deserialization in MLflow 0.5.0 through 3.4.0 allows remote attackers to execute code through a malicious PyTorch model. The mlflow.pytorch.load_model function passes attacker-controlled model.pth pickle data to torch.load, which reconstructs objects and invokes embedded reduction code. Execution occurs only when an end user retrieves and loads the uploaded model, and the payload runs with that user's privileges.
Summary
What happened
Unsafe deserialization in MLflow 0.5.0 through 3.4.0 allows remote attackers to execute code through a malicious PyTorch model. The mlflow.pytorch.load_model function passes attacker-controlled model.pth pickle data to torch.load, which reconstructs objects and invokes embedded reduction code. Execution occurs only when an end user retrieves and loads the uploaded model, and the payload runs with that user's privileges.
The record
- CVE
- CVE-2024-37059
- Published
- Jun 4, 2024
- Updated
- Aug 2, 2024
- Vendor
- MLflow Project
- Product
- MLflow
- Classifications
- CWE-502, T1204.002
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Jun 4, 2024CVE publishedPublication date reported by the CVE source.
- Aug 2, 2024Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=0.5.0 <=*
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
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.
Public exploit references
- HiddenLayer malicious PyTorch model demonstrationproof of concept · demonstrated
Labels summarize the accepted research assessment. They do not indicate a test against your environment.
Technologies
Your stack
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Your stack
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