Audience
Developers in search a solution to manage their fuzzing testing processes
About 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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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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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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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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go-fuzz
Go-fuzz is a coverage-guided fuzzing solution for testing Go packages. Fuzzing is mainly applicable to packages that parse complex inputs (both text and binary) and is especially useful for hardening systems that parse inputs from potentially malicious users (anything accepted over a network). go-fuzz has recently added preliminary support for fuzzing Go Modules. If you encounter a problem with modules, please file an issue with details. Data is a random input generated by go-fuzz, note that in most cases it is invalid. The function must return 1 if the fuzzer should increase the priority of the given input during subsequent fuzzing if the input must not be added to the corpus even if it gives new coverage, and 0 otherwise; other values are reserved for future use. The fuzz function must be in a package that go-fuzz can import. This means the code you want to test can't be in package main. Fuzzing internal packages is supported, however.
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Google
United States
google.github.io/clusterfuzz/
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