Book Image

Fuzzing Against the Machine

By : Antonio Nappa, Eduardo Blázquez
Book Image

Fuzzing Against the Machine

By: Antonio Nappa, Eduardo Blázquez

Overview of this book

Emulation and fuzzing are among the many techniques that can be used to improve cybersecurity; however, utilizing these efficiently can be tricky. Fuzzing Against the Machine is your hands-on guide to understanding how these powerful tools and techniques work. Using a variety of real-world use cases and practical examples, this book helps you grasp the fundamental concepts of fuzzing and emulation along with advanced vulnerability research, providing you with the tools and skills needed to find security flaws in your software. The book begins by introducing you to two open source fuzzer engines: QEMU, which allows you to run software for whatever architecture you can think of, and American fuzzy lop (AFL) and its improved version AFL++. You’ll learn to combine these powerful tools to create your own emulation and fuzzing environment and then use it to discover vulnerabilities in various systems, such as iOS, Android, and Samsung's Mobile Baseband software, Shannon. After reading the introductions and setting up your environment, you’ll be able to dive into whichever chapter you want, although the topics gradually become more advanced as the book progresses. By the end of this book, you’ll have gained the skills, knowledge, and practice required to find flaws in any firmware by emulating and fuzzing it with QEMU and several fuzzing engines.
Table of Contents (18 chapters)
1
Part 1: Foundations
5
Part 2: Emulation and Fuzzing
9
Part 3: Advanced Concepts
15
Chapter 12: Conclusion and Final Remarks

Summary

We saw, in this chapter, that QEMU is large and complex software that allows us to emulate different computer architectures, as well as run different systems implemented, thanks to dynamic recompilation (among other available technologies). QEMU has also played a crucial role in the world of cybersecurity as it has allowed the analyst to apply dynamic analysis, as well as fuzzing, to binaries from architectures different from the host architecture they are using (with the performance penalty that QEMU inevitably supposes), but even with its shortcomings, there’s a list of vulnerabilities that were found using this software as the base of the analysis. Finally, we saw that there are ways to interact with QEMU by writing our own code in C for the main software; these plugins allow us to easily interact and manage QEMU with easy-to use programming languages, such as Python. This will be important for future chapters, as it allows us to automate some of the tasks we will...