I’ve been doing application security long enough to get twitchy whenever a book has “AI” on the cover. Most of what crosses my desk in that genre is hype wearing a lab coat. Lots of talk about the future, very little you can use on a Monday morning. So I cracked open Steve Wilson’s The Developer’s Playbook for Large Language Model Security: Building Secure AI Applications expecting the usual letdown. I was wrong, and I’m glad to say so.
The reason it works is that Wilson didn’t write it for the keynote crowd. He wrote it for the person who just bolted an LLM onto a real product and is quietly wondering what they signed up for. He ran the OWASP Top 10 for LLM Applications effort, and you can feel that all through the book. If you’ve spent time with the classic OWASP Top 10 like I have, the layout feels like an old friend. Prompt injection, training data poisoning, sketchy output handling, excessive agency, and the rest each get their own treatment. He explains how the thing actually breaks, then talks about what you can really do about it instead of waving at a vendor.
What I appreciated most is that he treats prompt injection as the genuinely hard problem it is. He doesn’t pretend a clever system prompt makes it disappear. Anybody who has tried to “just filter the bad inputs” on a regular injection bug knows that game never ends, and the same logic applies here. Being honest about the limits of a mitigation is rarer than it should be, and it earned my trust early.
The chapters on excessive agency and overreliance hit home for me. We keep handing these models the keys, wiring them up to tools, plugins, and databases, and then acting surprised when one of them does exactly what an attacker nudged it to do. Wilson walks through how to put guardrails around what the model is allowed to touch, and that section alone is worth the price. He also spends real time on the supply chain side of things, which most people skip entirely. Where did your model come from? What’s in the training data? Who maintains the plugin you just installed? Those questions matter, and he doesn’t let you off the hook.
It isn’t perfect. The field moves so fast that a few specifics will go stale, and a seasoned appsec person will skim the foundational chapters. There’s also more “here’s how to think about it” than copy-paste code, but honestly that was the right call. The mindset outlives whatever framework is hot this quarter.
If you build anything that calls an LLM, or you got volunteered to review something that does, grab this one. It’s the closest thing I’ve found to a sane map of the territory, and it’ll save you from learning these lessons the hard way in production. Easy recommendation from me.
My rating: 4.5 out of 5.