Securing AI requires a system-level approach across models, data, identities, tools, infrastructure, and execution paths. This book shows how to apply Product Security and Secure SDLC principles to AI-enabled products, from RAG and agents to MCP, evaluations, supply chain risk, runtime controls, and governance, while building the fundamentals needed for a practical AI Product Security operating model.
A practical engineering guide to hardening Python Docker containers. Learn step-by-step how to implement rootless execution, drop dangerous Linux capabilities, and secure your production deployments.
Senior SDET work is architecture, not scripts. 18 chapters on Playwright and TypeScript at real scale — fixtures, API mocking, sharding, the Screenplay pattern — plus one Appium test driving both iOS and Android, schema-validated API testing, and performance end to end. Includes the complete, tested companion code, and 100% of author royalties fund peer-reviewed cancer-survivor research.