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Fuzzing Against the Machine

Fuzzing Against the Machine

By : Antonio Nappa, Eduardo Blázquez
4.5 (15)
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Fuzzing Against the Machine

Fuzzing Against the Machine

4.5 (15)
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)
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1
Part 1: Foundations
5
Part 2: Emulation and Fuzzing
9
Part 3: Advanced Concepts
15
Chapter 12: Conclusion and Final Remarks

Fuzzing and analysis techniques

Fuzzing is one of the most effective, yet extremely difficult to categorize, techniques to test software. You can imagine a kid using a computer in a very naïve way, which could be defined as fuzzing. Or, for instance, using random input directly from /dev/urandom in Linux may be considered fuzzing too. Using the help of my grandma to interact with a computer system could also be considered an effective technique to fuzz software. Fuzzing, by definition, does not only apply to running software but it can also be technically applied to source code and compiled code. Though, if we are not running the program, the term fuzzing may not be appropriate since we will fall into the static analysis domain. We can synthesize fuzzing and dynamic and static analysis into the definition of concolic testing, where concolic is a blend of the words concrete and symbolic. The aforementioned techniques are often used by many researchers together when trying to emulate...

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