The Developer's Playbook for Large Language Model Security

Preface

Everywhere in the world, we’re riding the large language model (LLM) wave, and it’s exhilarating! When ChatGPT burst onto the scene, it didn’t just walk into the record books; it smashed them, becoming the fastest-adopted application in history. Now, it’s as if every software vendor on the planet is racing to embed generative AI and LLM technologies into their stack, pushing us into uncharted territories. The buzz is real, the hype is justified, and the possibilities seem limitless.

But hold on because there’s a twist. As we marvel at these technological wonders, their security scaffolding is, to put it mildly, a work in progress. The hard truth? Many developers are stepping into this new era without a map, largely unaware of the security and safety quicksand beneath the surface. It’s almost routine now: every week, we’re hit with another headline screaming about an LLM hiccup. The fallout from these individual incidents has been moderate so far, but make no mistake—we’re flirting with disaster.

The risks aren’t just hypothetical; they’re as real as it gets, and the clock is ticking. Without a deep dive into the murky waters of LLM security risks and how to navigate them, we’re not just risking minor glitches; we’re courting major catastrophes. It’s time for developers to gear up, get informed, and get ahead of the curve. Fast!

Who Should Read This Book

The primary audience for this book is development teams that are building custom applications that embed LLM technologies. ...