Root code execution via untrusted weight deserialization
Published Dec 23, 2025 · Updated Dec 23, 2025
Deserialization in Tencent FaceDetection-DSFD allows remote attackers to execute code as root through a malicious pretrained-weight file. During ResNet initialization, model/resnet.py passes the configured model_path directly to torch.load, which deserializes the file without establishing that it is trusted. At affected commit 09deec4376f397a1124f71bc81210fadfaac296e, exploitation requires the target to open or load the crafted file, and successful payloads gain root-context execution.
Summary
What happened
Deserialization in Tencent FaceDetection-DSFD allows remote attackers to execute code as root through a malicious pretrained-weight file. During ResNet initialization, model/resnet.py passes the configured model_path directly to torch.load, which deserializes the file without establishing that it is trusted. At affected commit 09deec4376f397a1124f71bc81210fadfaac296e, exploitation requires the target to open or load the crafted file, and successful payloads gain root-context execution.
The record
- CVE
- CVE-2025-13715
- Published
- Dec 23, 2025
- Updated
- Dec 23, 2025
- Vendor
- Tencent
- Product
- FaceDetection-DSFD
- Classifications
- CWE-502, CAPEC-586, T1204.002
- 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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Is a vulnerable build present?
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- Affected versionversion=09deec4376f397a1124f71bc81210fadfaac296e
What conditions does exploitation require?
What is affected?
Published CVSS scores
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Attacks
What attackers are doing with it
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Weakness, pattern, technique
Public exploit references
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Technologies
Your stack
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Your stack
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