Review: The Developer’s Playbook for Large Language Model Security

With the adoption of large language models (LLMs) across industries, security teams often play catch-up. Many organizations are integrating GenAI into customer interactions, software development, and enterprise decision-making, often without grasping the security implications.

As LLMs are becoming integral to enterprise operations, The Developer’s Playbook for Large Language Model Security aims to be a timely resource for security professionals.

About the author

Steve Wilson, Chief Product Officer at Exabeam, and an expert with over 20 years of experience in AI, cybersecurity, and cloud computing, is a leader in advancing security best practices. As the founder and project leader at the OWASP Foundation, he spearheads the development of the “Top 10 List for Large Language Model Applications,” a resource for understanding GenAI security risks.

Practical approach to a growing security challenge

One of the book’s standout qualities is its hands-on, real-world perspective. Wilson doesn’t just highlight the risks, he dissects the mechanisms behind LLM vulnerabilities and provides actionable mitigation strategies. From prompt injection attacks to adversarial data poisoning, the book explores the most pressing security concerns surrounding LLMs.

A significant strength of the book is its direct connection to the OWASP Top 10 for LLM Applications project. Wilson walks readers through the collaborative process behind its creation, emphasizing that these security risks were not identified in isolation but vetted by a global network of experts. While the book is not an official OWASP product, it benefits from the same rigorous threat classification and mitigation approach.

This background is invaluable for security professionals. The book doesn’t just list risks, it contextualizes them within real-world deployments, ensuring that security teams can adapt these insights to their environments.

Key covered topics

• Security challenges of LLMs – Unlike traditional web applications, LLMs introduce new trust boundaries and attack surfaces that demand fresh security paradigms.
• The OWASP Top 10 for LLM Security – A deep dive into the most critical risks, including data leakage, prompt injections, and supply chain vulnerabilities.
• Defensive strategies – From runtime safeguards to input validation, Wilson provides security practitioners with techniques for hardening LLM-based systems.
• Case studies and emerging threats – The book draws from real-world breaches and misconfigurations, offering insights into how attackers are currently exploiting AI-driven applications.

Who is it for?

The book is structured in a way that makes it useful as both an introduction to LLM security and a reference guide for professionals. The Developer’s Playbook for Large Language Model Security is a must-read for any security professional safeguarding AI-driven applications. Its technical depth, practical strategies, and real-world case studies make it a relevant and actionable security book.