The Developer's Playbook for Large Language Model Security: Building Secure AI Applications

by Steve Wilson

Large language models (LLMs) are not just shaping the trajectory of AI, they're also unveiling a new era of security challenges. This practical book takes you straight to the heart of these threats. Author Steve Wilson, chief product officer at Exabeam, focuses exclusively on LLMs, eschewing generalized AI security to delve into the unique characteristics and vulnerabilities inherent in these models.

Complete with collective wisdom gained from the creation of the OWASP Top 10 for LLMs list—a feat accomplished by more than 400 industry experts—this guide delivers real-world guidance and practical strategies to help developers and security teams grapple with the realities of LLM applications. Whether you're architecting a new application or adding AI features to an existing one, this book is your go-to resource for mastering the security landscape of the next frontier in AI.

You'll

Why LLMs present unique security challenges How to navigate the many risk conditions associated with using LLM technology How to identify the top risks and vulnerabilities associated with LLMs Methods for deploying defenses to protect against attacks on top vulnerabilities And more!

Genres: Artificial Intelligence, Science, Technical, Nonfiction, Technology

200 pages, Paperback

Published October 29, 2024

Reviews

[Lucille Nguyen · Rating 4 out of 5]

Good general overview of LLM security. Has a good approach of viewing security in terms of a software supply chain, which then allows a generalization of supply chain risks to the software domain. General, but it is a "playbook" as the title says.

[Adrian · Rating 5 out of 5]

“LLM Application Security” is a serious attempt to organize the risks, threats, and protection methods for systems that use large language models (LLMs). The author takes on a tough job-explaining a fast-changing and still quite new field-in a step-by-step, example-based way, with a strong focus on real-world practice.

What I liked most were the many clear examples that make it easier to understand how attacks work and how to prevent them. The writing style reminded me of Adam Shostack’s famous book on threat modeling - both authors break things down clearly, using real cases to explain each type of threat. This is a big strength of the book.

The book doesn’t try to be trendy- it’s reliable and practical. It feels more like a solid training guide than a popular science book. But thanks to all the examples, it’s not boring. It feels like a smart colleague explaining a threat to you on a whiteboard, then showing you two real-life cases and a counterexample to help you understand the limits.

[Harald G. · Rating 3 out of 5]

Many rules of thumb for secure development and deployment of Large Language Models based on common sense, as well as some rules inferred from non-AI computer security.
Maybe this is one of the first books of its kind?

[Johnny · Rating 5 out of 5]

The book offers a good understanding of the many attack vectors a LLM faces. It not only shows how things can go bad, but what we can do to mitigate and reduce the attack surface. Definitely a must-read for everyone who puts an LLM in the world.

[Özgür · Rating 2 out of 5]

Very generic coverage of llm security...
Maybe more relevant for newcomers into the field. Otherwise not much to learn from...