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Building and Automating Penetration Testing Labs in the Cloud

Building and Automating Penetration Testing Labs in the Cloud

By : Joshua Arvin Lat
4.8 (13)
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Building and Automating Penetration Testing Labs in the Cloud

Building and Automating Penetration Testing Labs in the Cloud

4.8 (13)
By: Joshua Arvin Lat

Overview of this book

The significant increase in the number of cloud-related threats and issues has led to a surge in the demand for cloud security professionals. This book will help you set up vulnerable-by-design environments in the cloud to minimize the risks involved while learning all about cloud penetration testing and ethical hacking. This step-by-step guide begins by helping you design and build penetration testing labs that mimic modern cloud environments running on AWS, Azure, and Google Cloud Platform (GCP). Next, you’ll find out how to use infrastructure as code (IaC) solutions to manage a variety of lab environments in the cloud. As you advance, you’ll discover how generative AI tools, such as ChatGPT, can be leveraged to accelerate the preparation of IaC templates and configurations. You’ll also learn how to validate vulnerabilities by exploiting misconfigurations and vulnerabilities using various penetration testing tools and techniques. Finally, you’ll explore several practical strategies for managing the complexity, cost, and risks involved when dealing with penetration testing lab environments in the cloud. By the end of this penetration testing book, you’ll be able to design and build cost-effective vulnerable cloud lab environments where you can experiment and practice different types of attacks and penetration testing techniques.
Table of Contents (15 chapters)
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1
Part 1: A Gentle Introduction to Vulnerable-by-Design Environments
5
Part 2: Setting Up Isolated Penetration Testing Lab Environments in the Cloud
9
Part 3: Exploring Advanced Strategies and Best Practices in Lab Environment Design

Using generative AI tools for exploit code generation

Generative AI has taken the world by storm and has revolutionized various industries and creative fields. From generating images and videos to even simulating natural language conversations, generative AI has pushed the boundaries further on what’s possible in the realm of AI. Its ability to generate new and innovative content has sparked innovation across diverse fields and applications.

Note

Since this is not a book on AI and ML, we will limit our scope to the main topic and focus on practical applications and examples instead. If you are interested in learning more about AI and ML, there are tons of available resources online to help you get started. I have also written two books on ML (which is a subset of AI)—Machine Learning with Amazon SageMaker Cookbook and Machine Learning Engineering on AWS by Packt Publishing. Feel free to check these out if you want to learn more about how to build and deploy ML models...

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