advboxes/AdvBox

Health v2 · maintenance only

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Adoption not part of the score

1404 stars · 266 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

AdvBox is a Baidu open-source toolbox for generating adversarial examples that fool neural networks across frameworks like PaddlePaddle, PyTorch, TensorFlow, Keras, MxNet, and Caffe2. It also benchmarks model robustness and includes tools for detecting adversarial examples and studying data poisoning, with a zero-coding CLI for generating attacks.

Use cases

• generate adversarial examples to fool image classifiers
• benchmark the robustness of machine learning models
• test whether a cloud image classification service is vulnerable to attacks
• detect adversarial examples in large datasets
• study data poisoning attacks on ML models
• attack face recognition systems in research settings
• generate adversarial examples without writing code via CLI

When to choose

• you need a multi-framework adversarial attack toolbox with a zero-coding CLI
• you are doing AI security research on attack and defense of neural networks
• you want to benchmark model robustness against FGSM, DeepFool, and similar attacks
• you work in PaddlePaddle and need a lightweight adversarial SDK

When to avoid

• you need actively maintained tooling with recent updates and community support
• you want adversarial training defenses integrated into a modern training pipeline
• you need support for the latest PyTorch or TensorFlow versions out of the box

Facets

library · maturity maintenance

machine-learning security cli benchmarking machine-learning security deep-learning artificial-intelligence python cross-platform adversarial-examples adversarial-attacks adversarial-defense model-robustness paddlepaddle pytorch tensorflow fgsm deepfool data-poisoning

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