Hugging Face Transformers X-CLIP Checkpoint Conversion 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 checkpoints. 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-28308.

A vulnerability in the HuggingFace Transformers library, specifically in the Trainer class, allows for arbitrary code execution. The loadrngstate() method in src/transformers/trainer.py at line 3059 calls torch.load() without the weightsonly=True parameter. This issue affects all versions of the library supporting torch>=2.2 when used with PyTorch versions below 2.6, as the safeglobals() context manager provides no protection in these versions. An attacker can exploit this vulnerability by supplying a malicious checkpoint file, such as rngstate.pth, which can execute arbitrary code when loaded. The issue is resolved in version v5.0.0rc3.