AI Application Security Testing: A Hands-On Guide to LLM Security, Prompt Injection Testing, RAG Vulnerabilities, and AI Penetration Testing with Python
What happens when an AI assistant exposes confidential data, follows malicious instructions hidden in a document, or executes an unauthorized action? Is your AI application secure enough to prevent these threats?
As businesses adopt large language models, AI agents, and retrieval-augmented generation (RAG), new security vulnerabilities are emerging. Traditional security testing alone may not detect prompt injection, insecure AI integrations, sensitive data exposure, and agent tool misuse.
AI Application Security Testing is a practical guide to identifying, testing, and fixing vulnerabilities in AI-powered applications. Through Python examples, realistic scenarios, and hands-on exercises, you'll learn how to evaluate AI security risks and strengthen application defenses.
WHAT YOU WILL LEARN:
Understand AI application security fundamentals and common attack surfaces.
Build safe Python laboratories for AI penetration testing.
Identify and test direct and indirect prompt injection attacks.
Detect sensitive data exposure and unsafe LLM outputs.
Test RAG systems for unauthorized retrieval and document manipulation.
Evaluate AI API authentication, validation, and security controls.
Identify AI agent vulnerabilities and test tool misuse.
Explore AI security testing tools, including PyRIT and garak.
Automate security tests using Python and pytest.
Apply security fixes, verify remediation, and document findings.
Implement continuous AI security testing practices.
WHY YOU NEED THIS BOOK
This book goes beyond theory by connecting AI security concepts with practical testing techniques. You'll gain the knowledge to recognize vulnerabilities, understand their causes, evaluate security controls, and apply effective fixes.
Whether you're a penetration tester, cybersecurity professional, Python developer, AI engineer, or aspiring AI security specialist, this guide provides a structured path toward stronger AI application security skills.
AI SECURITY THREATS ARE EVOLVING. DON'T FALL BEHIND.
As AI becomes part of business-critical applications, the demand for professionals who understand AI security testing continues to grow. Building these skills today can help you prepare for tomorrow's security challenges.
Take the next step toward mastering AI application security testing.
Get your copy today and start developing the practical Python skills to identify vulnerabilities, test AI systems, and build stronger security defenses.
