Fuzzing: Brute Force Vulnerability Discovery -- Chapter 12, Fuzzing Frameworks

Although fuzzers are effective against a wide range of common applications, we often have a need for more customization and thorough fuzzing for proprietary and previously untested protocols. This is where fuzzing frameworks become extremely useful. In this chapter the authors explore a number of open source fuzzing frameworks, including SPIKE, Autodafé and GPF.

As a registered member of SearchSoftwareQuality.com, you're entitled to a complimentary copy of Chapter 12 of Fuzzing: Brute Force Vulnerability Discovery written by Michael Sutton, Adam Greene, and Pedram Amini and published by Addison-Wesley. Although fuzzers are effective against a wide range of common applications, we often have a need for more customization and thorough fuzzing for proprietary and previously untested protocols....

This is where fuzzing frameworks become extremely useful. In this chapter, "Fuzzing Frameworks," the authors explore a number of open source fuzzing frameworks, including SPIKE, Autodafé and GPF.



Fuzzing: Brute Force Vulnerability Discovery

Book description:
Fuzzing has evolved into one of today's most effective approaches to test software security. To "fuzz," you attach a program's inputs to a source of random data, and then systematically identify the failures that arise. Hackers have relied on fuzzing for years: Now, it's your turn. In this book, renowned fuzzing experts show you how to use fuzzing to reveal weaknesses in your software before someone else does.

Fuzzing is the first and only book to cover fuzzing from start to finish, bringing disciplined best practices to a technique that has traditionally been implemented informally. The authors begin by reviewing how fuzzing works and outlining its crucial advantages over other security testing methods. Next, they introduce state-of-the-art fuzzing techniques for finding vulnerabilities in network protocols, file formats, and Web applications; demonstrate the use of automated fuzzing tools; and present several insightful case histories showing fuzzing at work.

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This was first published in June 2007

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