AI / LLM Security — Beginner to Expert · modules
22 modules, theory + hands-on. Prompt injection, data poisoning, agent threat models, building your own AI, optimisation, and reverse-engineering trending products like Cursor & Perplexity.
AI Red Teaming — Methodology, PyRIT, garak, llm-guard
Red teaming an LLM is not penetration testing. There is no shell to pop, no service to enumerate. Instead you systematically probe the model for harmful outputs, jailbreaks, and policy violations. This module covers the methodology used by Microsoft AIRT, Anthropic, and OpenAI re
AI Code Generation Security — Copilot, Cursor, Cline Risks
Copilot, Cursor, Cline, and Claude Code generate millions of lines per day. They also leak code via context window, suggest insecure patterns, are vulnerable to prompt injection in source files, and act as data-exfiltration channels. This module covers the threats and the enginee
Self-Hosting Llama / Mistral / Qwen — vLLM vs Ollama vs llama.cpp Benchmarks
Three serious LLM runtimes, three different sweet spots. Ollama for developers and single-user. llama.cpp for edge and embedded. vLLM for production multi-user serving. This module benchmarks them on identical hardware, explains the architectural differences, and shows when to pi
Build Your Own ChatGPT Wrapper Safely — Architecture, Auth, Rate Limit, Logging
Half the SaaS launches in 2024-2025 were "ChatGPT for X." Most shipped with embarrassing security gaps: hardcoded API keys, no rate limiting, no abuse logging, prompt injection that leaks system prompts. This module is the production architecture for a chat wrapper that does not