Vulnerable code sample

import os
import torch
import argparse

# The script name would be neural_magic_training.py

def _load_model(model_path: str):
    """
    Loads a model from a given path. This function is vulnerable because it uses
    torch.load() without the 'weights_only=True' parameter, allowing for the
    deserialization of arbitrary Python objects.
    """
    print(f"Attempting to load model from: {model_path}")
    
    # Path to the potentially malicious state dictionary file
    state_dict_path = os.path.join(model_path, "state_dict.pt")

    if not os.path.exists(state_dict_path):
        raise FileNotFoundError(f"Could not find state_dict.pt in {model_path}")

    # VULNERABLE LINE: The 'weights_only' parameter is missing.
    # A malicious state_dict.pt file can now execute arbitrary code.
    state_dict = torch.load(state_dict_path)

    # The script would continue to use the loaded 'state_dict' here...
    print("Model state dictionary loaded.")
    # For demonstration, we just print the keys.
    # In a real scenario, this would be loaded into a model instance.
    print(f"Loaded keys: {state_dict.keys() if isinstance(state_dict, dict) else 'Object is not a dict'}")

if __name__ == "__main__":
    parser = argparse.ArgumentParser(
        description="Vulnerable model loading script demonstration."
    )
    parser.add_argument(
        "--model",
        type=str,
        required=True,
        help="Path to the model directory containing the state_dict.pt file.",
    )
    args = parser.parse_args()

    try:
        # Calling the vulnerable function with user-provided input
        _load_model(model_path=args.model)
        print("Script finished successfully.")
    except Exception as e:
        print(f"An error occurred during model loading: {e}")