ai-security-toolkit 1.1.2

A red-team AI security framework with adversarial attack modules

🛡️ AI Security Toolkit

A red-team framework for testing the vulnerabilities of AI models through adversarial attacks, privacy leakage, and model exploitation techniques — built and maintained by @rishit03.

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🚀 Features

✅ 5+ attack modules
✅ Unified logging and visualization
✅ Command-line interface (interactive menu)
✅ Modular, reusable, and pip-installable
✅ Built using TensorFlow, CleverHans, and Python's best practices

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📦 Modules Included

Module Name	Description
🔓 Adversarial Attack (FGSM)	Confuses the model with small pixel changes
💉 Label Flip Poisoning	Modifies training labels to reduce model accuracy
🧠 Membership Inference Attack	Infers if a data point was used in training
🪞 Model Inversion	Reconstructs training images from the model
🧬 Model Stealing	Clones the target model using black-box queries
🎯 Backdoor Trigger Attack	Embeds a hidden trigger that forces misclassification

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💻 CLI Usage

# After pip install or cloning locally
python ai_toolkit/run.py