Your AI Systems Are Already Being Hacked. Most Security Teams Don't Know How.
Something just changed in how attackers target organizations—and it has nothing to do with malware, phishing, or zero-days.
The new attack surface is the AI your company just deployed. The chatbot answering customer questions. The copilot reading your emails. The agent booking meetings, executing code, and writing to your database. Every one of these systems can be compromised with a sentence. No exploit kit. No binary payload. Just words—carefully chosen words that make the model do exactly what the attacker wants.
This is prompt injection. This is jailbreaking. This is the attack class that put Microsoft Copilot on the front page after researchers stole user data by sending a single email. The same class that caused ChatGPT to exfiltrate conversation history through a rendered image link. The same class that has gone from lab curiosity in 2022 to documented enterprise breach in 2026—and most security teams are still treating it as a quality problem, not an attack.
Hacking LLM-Powered Systems is the first practitioner's field guide built for the professional who needs to find these vulnerabilities before attackers do—and actually knows how to write up what they found.
This is not a survey. Every chapter teaches a technique you can run in your own authorized lab this week:
You will learn how to weaponize prompt injection across every delivery surface—user messages, RAG stores, emails, calendar events, and MCP tool descriptions. How to execute jailbreaks that bypass safety training through multi-turn escalation, persona manipulation, and structured-format abuse. How to induce hallucinations for supply-chain attacks and false grounding. How to exploit AI agents through confused-deputy attacks, SSRF through tool calls, memory poisoning that survives across sessions, and agent-to-agent trust abuse. And how to assemble a complete end-to-end kill chain that moves from a poisoned document in a knowledge base to credential exfiltration—triggered by a normal user asking a normal question.
Every attack maps to OWASP LLM Top 10 2025, OWASP Agentic Top 10 2026, and MITRE ATLAS v5.1.0—the frameworks your engineering team, your CISO, and your compliance function already speak.
The 30-Day Red Team Project is where everything becomes real. Five hands-on phases walk you through building an isolated lab, deploying a self-hosted RAG chatbot, running a full injection campaign, automating jailbreaks with PyRIT, Garak, and Promptfoo, adding tools and memory to create a two-agent target, and executing the complete lethal-trifecta kill chain—start to finish, against a system you built and understand completely. No guesswork. No simulations. Real findings, real evidence, real regression tests you can hand to an engineering team.
By the time you close this book, you will have run the attacks, written the findings in a format that gets fixed, and built the automated test suite that keeps them fixed.
The window to become the person who understands AI security—not just at the concept level but at the terminal level—is open right now. The organizations deploying AI agents are moving fast. The attackers studying those agents are moving faster. The practitioners who can bridge that gap—who can find the kill chain, measure the blast radius, and communicate it in language both engineers and executives act on—are in short supply and high demand.
This book puts you in that group.
Perfect for: Security engineers, penetration testers, red teamers, AI/ML engineers, application security professionals, and developers building or securing LLM-powered systems.
