An open-source knowledge base of defensive countermeasures to protect AI/ML systems. Features interactive views and maps defenses to known threats from frameworks like MITRE ATLAS, MAESTRO, and OWASP.

Reading list for adversarial perspective and robustness in deep reinforcement learning.

XSSGAI is the first-ever AI-powered XSS (Cross-Site Scripting) payload generator. It leverages machine learning and deep learning to create novel payloads based on patterns from real-world XSS attacks.

Do you want to learn AI Security but don't know where to start ? Take a look at this map.

A hybrid Solidity + Python security toolkit that analyzes ERC-20 token contracts using static pattern extraction and ML-inspired scoring. Detects mint backdoors, blacklist controls, fee manipulation, trading locks, and rugpull mechanics. Outputs interpretable risk scores, labels, and structured features for deeper analysis.

Measure and Boost Backdoor Robustness

A curated collection of privacy-preserving machine learning techniques, tools, and practical evaluations. Focuses on differential privacy, federated learning, secure computation, and synthetic data generation for implementing privacy in ML workflows.

AAAI 2025 Tutorial on AI Safety

Educational research demonstrating weight manipulation attacks in SafeTensors models. Proves format validation alone is insufficient for AI model security.

Blockchain enabled Adversarial Threat Intelligence Sharing for Robust Ransomware Detection in air gaps

Interactive Jupyter demo of Prisma AIRS detecting pickle deserialization attacks (CWE-502) in ML models. Educational security demonstration with ROI analysis.

Minimal reproducible PoC of 3 ML attacks (adversarial, extraction, membership inference) on a credit scoring model. Includes pipeline, visualizations, and defenses

A learning-focused simulation of adversarial attacks against ML-based network intrusion detection systems within a Zero-Trust architecture, including constrained adversarial modeling, policy enforcement, and security-focused evaluation metrics.

Code for "On the Privacy Effect of Data Enhancement via the Lens of Memorization"

Testing adversarial ML attacks (data poisoning, targeted misclassification, and model extraction) and discussing defensive tradeoffs that exist for real deployments.

AI-powered advanced web application firewall using machine learning – Final Year Project (CSE)

Control a 5-DOF Lynxmotion robotic arm using a vision language model for object detection and task planning

This is a software framework that can be used for the evaluation of the robustness of Malware Detection methods with respect to adversarial attacks.

AI Infrastructure Security Engineer Learning Track - ML infrastructure security, model security, and compliance

ML-powered threat detection and alert correlation platform for enterprise security monitoring.