Audience
Anyone searching for a curated list of resources to learn about fuzzing and development
About Awesome Fuzzing
Awesome Fuzzing is a list of fuzzing resources including books, courses, both free and paid, videos, tools, tutorials, and vulnerable applications to practice in order to learn fuzzing and initial phases of exploit development like root cause analysis. Courses/training videos on fuzzing, videos talking about fuzzing techniques, tools, and best practices. Conference talks and tutorials, blogs, tools that help in fuzzing applications, and fuzzers that help in fuzzing applications that use network-based protocols like HTTP, SSH, SMTP, etc. Search and pick the exploits, that have respective apps available for download, and reproduce the exploit by using the fuzzer of your choice. Set of tests for fuzzing engines. Includes different well-known bugs. A corpus, including various file formats for fuzzing multiple targets in the fuzzing literature.
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ClusterFuzz
ClusterFuzz is a scalable fuzzing infrastructure that finds security and stability issues in software. Google uses ClusterFuzz to fuzz all Google products and as the fuzzing backend for OSS-Fuzz. ClusterFuzz provides many features to seamlessly integrate fuzzing into a software project’s development process. Fully automatic bug filing, triage, and closing for various issue trackers. Supports multiple coverages guided fuzzing engines for optimal results (with ensemble fuzzing and fuzzing strategies). Statistics for analyzing fuzzer performance, and crash rates. Easy to use web interface for management and viewing crashes. Support for various authentication providers using Firebase. Support for black-box fuzzing, test case minimization, and regression finding through bisection.
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Peach Fuzzer
Peach is a SmartFuzzer that is capable of performing both generation and mutation-based fuzzing. Peach requires the creation of Peach Pit files that define the structure, type information, and relationships in the data to be fuzzed. It additionally allows for the configuration of a fuzzing run including selecting a data transport (publisher), logging interface, etc. Peach has been under active development since 2004 and is in its third major version. Fuzzing continues to be the fastest way to find security issues and test for bugs. Effective hardware fuzzing with Peach will introduce students to the fundamentals of device fuzzing. Peach was designed to fuzz any type of data consumer from servers to embedded devices. Researchers, corporations, and governments already use Peach to find vulnerabilities in hardware. This course will focus on using Peach to target embedded devices and collect information from the device in the event of a crash.
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LibFuzzer
LibFuzzer is an in-process, coverage-guided, evolutionary fuzzing engine. LibFuzzer is linked with the library under test, and feeds fuzzed inputs to the library via a specific fuzzing entry point (or target function); the fuzzer then tracks which areas of the code are reached, and generates mutations on the corpus of input data in order to maximize the code coverage. The code coverage information for libFuzzer is provided by LLVM’s SanitizerCoverage instrumentation. LibFuzzer is still fully supported in that important bugs will get fixed. The first step in using libFuzzer on a library is to implement a fuzz target, a function that accepts an array of bytes and does something interesting with these bytes using the API under test. Note that this fuzz target does not depend on libFuzzer in any way so it is possible and even desirable to use it with other fuzzing engines like AFL and/or Radamsa.
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Google ClusterFuzz
ClusterFuzz is a scalable fuzzing infrastructure that finds security and stability issues in software. Google uses ClusterFuzz to fuzz all Google products and as the fuzzing backend for OSS-Fuzz. ClusterFuzz provides many features to seamlessly integrate fuzzing into a software project’s development process. Fully automatic bug filing, triage, and closing for various issue trackers. Supports multiple coverages guided fuzzing engines for optimal results (with ensemble fuzzing and fuzzing strategies). Statistics for analyzing fuzzer performance, and crash rates. Easy to use web interface for management and viewing crashes. Support for various authentication providers using Firebase. Support for black-box fuzzing, test case minimization, and regression finding through bisection.
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Pricing
Starting Price:
Free
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Free Version available.
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secfigo
github.com/secfigo/Awesome-Fuzzing
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