CVE-2025-14930
Unknown Unknown - Not Provided
Deserialization RCE in Hugging Face Transformers GLM4 Weights Parsing

Publication date: 2025-12-23

Last updated on: 2025-12-23

Assigner: Zero Day Initiative

Description
Hugging Face Transformers GLM4 Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of weights. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-28309.
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Meta Information
Published
2025-12-23
Last Modified
2025-12-23
Generated
2026-05-07
AI Q&A
2025-12-23
EPSS Evaluated
2026-05-05
NVD
Affected Vendors & Products
Showing 1 associated CPE
Vendor Product Version / Range
hugging_face transformers *
Helpful Resources
Exploitability
CWE
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KEV
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CWE ID Description
CWE-502 The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?

This vulnerability is a remote code execution flaw in the Hugging Face Transformers library, specifically in the GLM4 model's deserialization process. It occurs because the software does not properly validate user-supplied data when parsing model weights, allowing an attacker to deserialize untrusted data. Exploiting this requires user interaction, such as visiting a malicious webpage or opening a malicious file, and enables the attacker to execute arbitrary code within the current process. [1]


How can this vulnerability impact me? :

If exploited, this vulnerability allows an attacker to execute arbitrary code on your system within the context of the affected process. This can lead to full compromise of confidentiality, integrity, and availability of the system or data handled by the Hugging Face Transformers library. Since exploitation requires user interaction, the risk involves users opening malicious files or visiting malicious websites, potentially leading to unauthorized control or damage. [1]


What immediate steps should I take to mitigate this vulnerability?

To mitigate this vulnerability, avoid opening untrusted files or visiting untrusted webpages that may trigger the deserialization of malicious data in the Hugging Face Transformers GLM4 model. Additionally, ensure that your installation of the Hugging Face Transformers library is updated with any patches or fixes provided by the vendor addressing this vulnerability. [1]


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