huggingface/transformers vulnerabilities

A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization by overriding the trust_remote_code parameter with untrusted configuration data.

All versions of the HuggingFace transformers library prior to 5.3.0 contain a critical remote code execution vulnerability. An attacker can craft a malicious config.json file with the _attn_implementation_internal field set to an attacker-controlled HuggingFace Hub repository ID. When a victim loads the model via AutoModelForCausalLM.from_pretrained(), the library downloads and executes arbitrary Python code from the attacker's repository with full OS privileges.

The huggingface/transformers library, versions prior to 4.53.0, is vulnerable to Regular Expression Denial of Service (ReDoS) in the AdamWeightDecay optimizer. The _do_use_weight_decay method processes user-controlled regular expressions, which can cause catastrophic backtracking and 100% CPU utilization.