Complete AI-powered security training with 40+ labs, CTF challenges, and realistic DFIR datasets. Learn ML threat detection, LLM analysis, adversarial ML, cloud security, and digital forensics. Beginner to expert.

Noise Injection Techniques provides a comprehensive exploration of methods to make machine learning models more robust to real-world bad data. This repository explains and demonstrates Gaussian noise, dropout, mixup, masking, adversarial noise, and label smoothing, with intuitive explanations, theory, and practical code examples.

Comprehensive taxonomy of AI security vulnerabilities, LLM adversarial attacks, prompt injection techniques, and machine learning security research. Covers 71+ attack vectors including model poisoning, agentic AI exploits, and privacy breaches.

Bug bounty report demonstrating prompt injection and command execution vulnerabilities in Meta AI's Instagram Group Chat

Master's students in NCCU SoSLab maintaining a cleaned and restructured version of INCITE (based on PyCT).

🛡️ Discover and analyze critical vulnerabilities in Meta AI's Instagram Group Chat, ensuring robust security through comprehensive testing and reporting.

A curated list of awesome resources for AI system security.

Adversarial ML Scanner for threat detection and ML backdoor attcaks

Security Vulnerabilities and Defensive Mechanisms in CLI/Terminal-Based Large Language Model Deployments - A Comprehensive Research Synthesis (Technical Report, November 2025)

Hybrid Threat Intelligence Engine with Explainable AI (XAI) and Automated Triage.

Placeholder for Annotated Research Papers in Deep learning discussed in Blog Posts. Most of the papers related to Adversarial ML and GAN.

A collection of resources documenting my research and learning journey in AI System Security.

Hybrid Threat Intelligence Engine with Explainable AI (XAI) and Automated Triage.

Autonomous adversarial agents that debate and debug code before you see it.

Fork for my contributions on Trojans, Comprehensive course materials covering ML safety, robustness, and AI alignment

An experiment in backdooring a shell safety classifier by planting a hidden trigger in its training data.

A Gemini-powered explainable AI assistant that analyzes and interprets anomalies in IoT power signals using RAG, few-shot prompting, and embeddings. Built during the 2025 Google GenAI Capstone.

🔍 Analyze security vulnerabilities in CLI-based LLM deployments, drawing insights from 95 peer-reviewed sources to enhance AI tool safety.

Meta AI Bug Bounty focuses on vulnerabilities in Instagram's Group Chat feature, revealing critical security risks. Join us in improving AI safety and explore our findings on GitHub! 🐙✨