Introduction¶

OpenAttack is an open-source Python-based textual adversarial attack toolkit, which handles the whole process of textual adversarial attacking, including preprocessing text, accessing the victim model, generating adversarial examples and evaluation.

Features & Uses¶

OpenAttack has the following features:¶

⭐️ Support for all attack types. OpenAttack supports all types of attacks including sentence-/word-/character-level perturbations and gradient-/score-/decision-based/blind attack models;

⭐️ Multilinguality. OpenAttack supports English and Chinese now. Its extensible design enables quick support for more languages;

⭐️ Parallel processing. OpenAttack provides support for multi-process running of attack models to improve attack efficiency;

⭐️ Compatibility with 🤗 Hugging Face. OpenAttack is fully integrated with 🤗 Transformers and Datasets libraries;

⭐️ Great extensibility. You can easily attack a customized victim model on any customized dataset or develop and evaluate a customized attack model.

OpenAttack has a wide range of uses, including:¶

✅ Providing various handy baselines for attack models;

✅ Comprehensively evaluating attack models using its thorough evaluation metrics;

✅ Assisting in quick development of new attack models with the help of its common attack components;

✅ Evaluating the robustness of a machine learning model against various adversarial attacks;

✅ Conducting adversarial training to improve robustness of a machine learning model by enriching the training data with generated adversarial examples.