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AI Security in Practice AI Security in Practice

AI Security in Practice

Deep technical implementation guides for securing AI systems in production. The practitioner layer between vendor marketing and unreadable PDFs.
Read the Manifesto GitHub
Foundations Start here. LLM internals, OWASP Top 10, tool selection, and your first security lab.
Attack and Red Team Prompt injection, jailbreaking, red teaming tools, adversarial ML, and CTFs.
Defend and Harden Guardrails, secure RAG, output validation, MCP security, and agent hardening.
Architecture and Platform Cloud AI security, MLOps, API gateway patterns, and Zero Trust for AI.
Governance, Risk and Compliance Frameworks, compliance, risk registers, incident response, and UK Government guidance.
Emerging Threats and Research AI worms, sleeper agents, supply chain attacks, and multi-agent system security.