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)
Part 1: Foundations
Part 2: Emulation and Fuzzing
Part 3: Advanced Concepts
Chapter 12: Conclusion and Final Remarks

Full-system fuzzing – introducing TriforceAFL

As previously mentioned, TriforceAFL is a tool that combines the capabilities of two powerful tools, AFL and QEMU, to apply fuzzing at the kernel level of an OS. In this section, we will delve deeper into the internals of TriforceAFL to understand how it works.

AFL utilizes modified versions of gcc, g++, clang, or clang++ during compilation to instrument the code at the entrance and exits of basic code blocks. These basic blocks are pieces of code with no branches or other conditions that may divert the control flow and thus execute in sequence. This instrumentation makes it easier to understand crash dumps and backtrack the stack when the fuzzed program reports a crash. An instrumented binary contains the necessary code for applying fuzzing and tracking program edge cases for code coverage. Given a set of inputs, AFL executes the binary executable program and collects traces and possible crashes. AFL then applies different mutation...