Code execution via unrestricted PyTorch checkpoint loading
Published Dec 23, 2025 · Updated Dec 23, 2025
Deserialization in Tencent NeuralClassifier Current allows context-dependent attackers to execute arbitrary code through a malicious checkpoint file. The _load_checkpoint function passes the file directly to torch.load without weights_only=True, permitting embedded Python objects to execute during loading. Execution requires a user to open the crafted checkpoint through the prediction workflow; payloads run with the application's privileges, reported as root on affected installations.
Summary
What happened
Deserialization in Tencent NeuralClassifier Current allows context-dependent attackers to execute arbitrary code through a malicious checkpoint file. The _load_checkpoint function passes the file directly to torch.load without weights_only=True, permitting embedded Python objects to execute during loading. Execution requires a user to open the crafted checkpoint through the prediction workflow; payloads run with the application's privileges, reported as root on affected installations.
The record
- CVE
- CVE-2025-13708
- Published
- Dec 23, 2025
- Updated
- Dec 23, 2025
- Vendor
- Tencent
- Product
- NeuralClassifier
- Classifications
- CWE-502, T1203
- Attack vector
- local
- Privileges
- unauthenticated
Timeline
How it unfolded
- Dec 23, 2025CVE publishedPublication date reported by the CVE source.
- Dec 23, 2025Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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- Affected versionversion=Current
What conditions does exploitation require?
What is affected?
Published CVSS scores
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Attacks
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Weakness, pattern, technique
Public exploit references
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Technologies
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Your stack
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