Torchattacks provides a PyTorch-compatible interface for running adversarial attacks against deep learning models. It implements standard attack methods like PGD and FGSM that perturb inputs to test model robustness. The library integrates directly with PyTorch models and is used for security research and evaluating defensive techniques.