دانلود کتاب امنیت LLM بومی هوش مصنوعی

AI-Native LLM Security serves as a comprehensive guide to navigating the complex intersection of arti cial intelligence and cybersecurity. As organizations race to integrate large language models (LLMs) into their products, the attack surface has expanded from traditional soware vulnerabilities to include novel threats like prompt injection, model poisoning, and agentic exploitation. Because this book project began almost two years ago, which is a lifetime in the fast-moving world of AI, we have dedicated speci c appendices to the very latest developments, ensuring you have immediate access to the 2025 OWASP Top 10 updates and the emerging AIVSS framework for agentic risks alongside the foundational core chapters. is book bridges the gap between data science and information security, offering a theoretical foundation for how these models function and a practical framework for securing them. e journey begins by demystifying the mechanics of LLMs and establishing the unique trust boundaries required for AI architectures. It then anchors the reader in the industry-standard OWASP Top 10 for LLM Applications, providing deep dives into speci c risks, mitigation strategies, and compliance alignments. As the book progresses, it moves from theory to active defense, covering secure system design, DevSecOps for AI, and operational resilience. By the end, readers will possess the knowledge to architect, build, and defend robust AI systems that can withstand both inherent model failures and sophisticated external attacks.