Fuzzing

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Fuzzing

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Author : Michael Sutton
language : en
Publisher: Pearson Education
Release Date : 2007-06-29

Fuzzing written by Michael Sutton and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-29 with Computers categories.

This is the eBook version of the printed book. If the print book includes a CD-ROM, this content is not included within the eBook version. FUZZING Master One of Today’s Most Powerful Techniques for Revealing Security Flaws! 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. Coverage includes: • Why fuzzing simplifies test design and catches flaws other methods miss • The fuzzing process: from identifying inputs to assessing “exploitability” • Understanding the requirements for effective fuzzing • Comparing mutation-based and generation-based fuzzers • Using and automating environment variable and argument fuzzing • Mastering in-memory fuzzing techniques • Constructing custom fuzzing frameworks and tools • Implementing intelligent fault detection Attackers are already using fuzzing. You should, too. Whether you’re a developer, security engineer, tester, or QA specialist, this book teaches you how to build secure software.

Fuzzing For Software Security Testing And Quality Assurance

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Author : Ari Takanen
language : en
Publisher: Artech House
Release Date : 2008

Fuzzing For Software Security Testing And Quality Assurance written by Ari Takanen and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.

Introduction -- Software vulnerability analysis -- Quality assurance and testing -- Fuzzing metrics -- Building and classifying fuzzers -- Target monitoring -- Advanced fuzzing -- Fuzzer comparison -- Fuzzing case studies.

Open Source Fuzzing Tools

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Author : Noam Rathaus
language : en
Publisher: Elsevier
Release Date : 2011-04-18

Open Source Fuzzing Tools written by Noam Rathaus and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-18 with Computers categories.

Fuzzing is often described as a “black box software testing technique. It works by automatically feeding a program multiple input iterations in an attempt to trigger an internal error indicative of a bug, and potentially crash it. Such program errors and crashes are indicative of the existence of a security vulnerability, which can later be researched and fixed. Fuzz testing is now making a transition from a hacker-grown tool to a commercial-grade product. There are many different types of applications that can be fuzzed, many different ways they can be fuzzed, and a variety of different problems that can be uncovered. There are also problems that arise during fuzzing; when is enough enough? These issues and many others are fully explored. Fuzzing is a fast-growing field with increasing commercial interest (7 vendors unveiled fuzzing products last year). Vendors today are looking for solutions to the ever increasing threat of vulnerabilities. Fuzzing looks for these vulnerabilities automatically, before they are known, and eliminates them before release. Software developers face an increasing demand to produce secure applications---and they are looking for any information to help them do that.

Fuzzing For Software Security Testing And Quality Assurance Second Edition

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Author : Ari Takanen,
language : en
Publisher: Artech House
Release Date : 2018-01-31

Fuzzing For Software Security Testing And Quality Assurance Second Edition written by Ari Takanen, and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-31 with Computers categories.

This newly revised and expanded second edition of the popular Artech House title, Fuzzing for Software Security Testing and Quality Assurance, provides practical and professional guidance on how and why to integrate fuzzing into the software development lifecycle. This edition introduces fuzzing as a process, goes through commercial tools, and explains what the customer requirements are for fuzzing. The advancement of evolutionary fuzzing tools, including American Fuzzy Lop (AFL) and the emerging full fuzz test automation systems are explored in this edition. Traditional software programmers and testers will learn how to make fuzzing a standard practice that integrates seamlessly with all development activities. It surveys all popular commercial fuzzing tools and explains how to select the right one for software development projects. This book is a powerful new tool to build secure, high-quality software taking a weapon from the malicious hacker’s arsenal. This practical resource helps engineers find and patch flaws in software before harmful viruses, worms, and Trojans can use these vulnerabilities to rampage systems. The book shows how to make fuzzing a standard practice that integrates seamlessly with all development activities.

Performant Binary Fuzzing Without Source Code Using Static Instrumentation

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Author : Eric Pauley
language : en
Publisher:
Release Date : 2019

Performant Binary Fuzzing Without Source Code Using Static Instrumentation written by Eric Pauley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

Fuzz testing (fuzzing), a technique for automatically finding exploitable bugs in programs, has seen increased popularity in the security community. While fuzzing techniques can efficiently discover new program behavior, modern fuzzing techniques are largely limited to the analysis of programs with source code available. We investigate the application of state-of-the-art fuzzing techniques to binary programs without source code, using static binary rewriting to modify the programs without recompiling them. Our tool, ReFuzz, allows off-the-shelf binaries to be analyzed using fuzzing techniques that were previously limited to source code. We evaluate our tool against source-available and binary-level fuzzers, and find that ReFuzz can discover similar and, in some cases, more bugs than a recently-published source-level fuzzer. Our work demonstrates the value of binary analysis techniques for fuzzing, and realizes a tool that will allow the security community to meaningfully analyze more software.

Fuzzing Against The Machine

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Author : Antonio Nappa
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-05-19

Fuzzing Against The Machine written by Antonio Nappa and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-19 with Computers categories.

Find security flaws in any architecture effectively through emulation and fuzzing with QEMU and AFL Purchase of the print or Kindle book includes a free PDF eBook Key Features Understand the vulnerability landscape and useful tools such as QEMU and AFL Explore use cases to find vulnerabilities and execute unknown firmware Create your own firmware emulation and fuzzing environment to discover vulnerabilities Book Description 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. What you will learn Understand the difference between emulation and virtualization Discover the importance of emulation and fuzzing in cybersecurity Get to grips with fuzzing an entire operating system Discover how to inject a fuzzer into proprietary firmware Know the difference between static and dynamic fuzzing Look into combining QEMU with AFL and AFL++ Explore Fuzz peripherals such as modems Find out how to identify vulnerabilities in OpenWrt Who this book is for This book is for security researchers, security professionals, embedded firmware engineers, and embedded software professionals. Learners interested in emulation, as well as software engineers interested in vulnerability research and exploitation, software testing, and embedded software development will also find it useful. The book assumes basic knowledge of programming (C and Python); operating systems (Linux and macOS); and the use of Linux shell, compilation, and debugging.

The Application Of Fuzzing In Software Product Line Testing

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Author : Dominik Aust
language : en
Publisher:
Release Date : 2023

The Application Of Fuzzing In Software Product Line Testing written by Dominik Aust and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.

Advanced Fuzzing Method For Software Security

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Author : Rui Zhong
language : en
Publisher:
Release Date : 2023

Advanced Fuzzing Method For Software Security written by Rui Zhong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.

Fuzzing is an increasingly popular technique for testing software functionality and identifying security weaknesses. Recent research has primarily focused on improving the effectiveness and efficiency of fuzzing. To make fuzzing more effective, researchers apply different methods, such as diverse initial seeds, varied mutation strategies, and different feedback to help produce better test cases. To make fuzzing more efficient, many research projects design specialized operating systems or parallel fuzzers to speed up the fuzzing process and accelerate bug detection. However, there are still some limitations in current fuzzing approaches. Firstly, most existing approaches, mutation-based and generation-based, have problems in exploring program states for software that requires structural input, especially when considering syntax and semantics. Mutation-based fuzzers lack an understanding of the test case format, often resulting in broken test cases and wasted time. Generation-based ones do not utilize feedback, such as code coverage, to guide the program state exploration, leading to repetitive testing of the same part of the code. Secondly, while parallel fuzzing is widely adopted to speed up bug detection, existing parallel approaches are built on top of synchronous serial fuzzers and rely on periodic synchronization to enable collaboration among multiple instances. The serial design of the fuzzer might waste CPU power due to blocking I/O operations. Additionally, the synchronization of fuzzing states between multiple instances presents a challenge, as untimely synchronization can result in suboptimal strategies while synchronizing too frequently creates excessive overhead. To address the first limitation, we turn our attention to language processors, such as compilers and interpreters, as they require inputs following specific syntactic and semantic rules. To effectively fuzz language processors, we are required to not only generate high-quality test cases for them, but also find a unified way to handle the different features, such as syntax and semantics, in multiple languages. As our first step, we focus on Database Management Systems (DBMSs) since they take a domain-specific language, Structure Query Language (SQL), as input. Empirical study shows that the syntactic and semantic accuracy of test cases is crucial for detecting bugs in DBMSs, especially those hidden within complex logic. Therefore, we design a fuzzing framework called Squirrel that uses a lightweight IR to generate syntactically correct SQL test cases and utilizes an instantiator to validate the test cases for DBMSs. By conducting experiments with real-world DBMSs, the results demonstrate that Squirrel not only produces accurate test cases but also has the ability to detect bugs in deep logic. Then, we generalize our approaches used for DBMS fuzzing and build a generic language processor fuzzing framework called PolyGlot. Our framework takes the specification of a language as input and casts it to IR's specification. Test cases are then transformed into IR statements, removing any language differences, followed by mutations and validations. Evaluation of PolyGlot shows that it can generate high-quality inputs to test various language processors and effectively detect bugs. To address the second limitation, we investigate the current parallel fuzzing architecture and introduce [mu]Fuzz, a microservice-based fuzzing framework. [mu]Fuzz breaks the serial fuzzing loops into concurrent services, each with multiple workers, making more efficient use of CPU power. Besides, [mu]Fuzz eliminates the synchronization of fuzzing states by partitioning the states across different services, allowing for optimal global decision-making. Our research focuses on enhancing the current fuzzing approaches in both effectiveness and efficiency. We design Squirrel and PolyGlot to improve fuzzing effectiveness by producing high-quality test cases that require structural formats. Moreover, we introduce [mu]Fuzz as the first attempt to improve fuzzing efficiency through the implementation of microservice architecture. More importantly, we have found 239 newly identified bugs and got 30 CVEs assigned, demonstrating the practicality of our methods in testing real-world software.

A Framework For File Format Fuzzing With Genetic Algorithms

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Author : Roger Lee Seagle
language : en
Publisher:
Release Date : 2012

A Framework For File Format Fuzzing With Genetic Algorithms written by Roger Lee Seagle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.

Secure software, meaning software free from vulnerabilities, is desirable in today's marketplace. Consumers are beginning to value a product's security posture as well as its functionality. Software development companies are recognizing this trend, and they are factoring security into their entire software development lifecycle. Secure development practices like threat modeling, static analysis, safe programming libraries, run-time protections, and software verification are being mandated during product development. Mandating these practices improves a product's security posture before customer delivery, and these practices increase the difficulty of discovering and exploiting vulnerabilities. Since the 1980's, security researchers have uncovered software defects by fuzz testing an application. In fuzz testing's infancy, randomly generated data could discover multiple defects quickly. However, as software matures and software development companies integrate secure development practices into their development life cycles, fuzzers must apply more sophisticated techniques in order to retain their ability to uncover defects. Fuzz testing must evolve, and fuzz testing practitioners must devise new algorithms to exercise an application in unexpected ways. This dissertation's objective is to create a proof-of-concept genetic algorithm fuzz testing framework to exercise an application's file format parsing routines. The framework includes multiple genetic algorithm variations, provides a configuration scheme, and correlates data gathered from static and dynamic analysis to guide negative test case evolution. Experiments conducted for this dissertation illustrate the effectiveness of a genetic algorithm fuzzer in comparison to standard fuzz testing tools. The experiments showcase a genetic algorithm fuzzer's ability to discover multiple unique defects within a limited number of negative test cases. These experiments also highlight an application's increased execution time when fuzzing with a genetic algorithm. To combat increased execution time, a distributed architecture is implemented and additional experiments demonstrate a decrease in execution time comparable to standard fuzz testing tools. A final set of experiments provide guidance on fitness function selection with a CHC genetic algorithm fuzzer with different population size configurations.

Network Protocol Fuzzing Based On Range Analysis

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Author : Shin Hyung Kang
language : en
Publisher:
Release Date : 2012

Network Protocol Fuzzing Based On Range Analysis written by Shin Hyung Kang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.

As networked computing devices have been widely used in recent years, this pervasive trend accelerates the development of new networked applications for mobile devices and corresponding applications for service servers. Simultaneously, the vulnerability issues for such applications have become more salient in the software security community. Networked applications, in which a large portion of their code execution depends on the network messages that they received, are the common cause of software vulnerabilities, since they are susceptible to attack via Internet. Consequently, it is essential to ensure the absence of exploitable vulnerabilities prior to the release of these applications. Fuzzing is the automated software testing technique that involves the generation of unexpected or random data to input for target applications. In its nature, fuzzing requires a long time taken to generate a variety of input data, and tends to miss exercising branch target blocks where networked applications commonly have vulnerable code segments. This is because most randomly generated input data does not meet the multiple conditionals in the codes. In this context, we propose an effective fuzz testing approach, which applies static analysis of the target source code to generate fuzzing constraints for the rapid exposure of the vulnerabilities. Specifically, our approach depends on range analysis algorithms among static analysis techniques to extract fuzzing constraints specific to target programs. This automated approach reduces both intricate calculations for solving constraints, and the time cost taken to test target programs. We perform the experiments against two target applications by using the new fuzzer design based on the Modified Range Analysis pass. The empirical results show that our approach can be generalized to other applications, and it reduces time cost during the fuzzing process.