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What is go-fuzz?

Go-fuzz is a specialized fuzzing tool that utilizes coverage guidance to effectively test Go packages, making it particularly adept at handling complex inputs, whether they are textual or binary. This type of testing is essential for fortifying systems that must manage data from potentially unsafe sources, such as those arising from network interactions. Recently, go-fuzz has rolled out preliminary support for fuzzing Go Modules, encouraging users to report any issues they experience along with comprehensive details. The tool creates random input data, which is frequently invalid, and if a function returns a value of 1, it prompts the fuzzer to prioritize that input for subsequent tests, though it should not be included in the corpus, even if it reveals new coverage; conversely, a return value of 0 indicates the opposite, while other return values are earmarked for future improvements. It is necessary for the fuzz function to be placed within a package recognized by go-fuzz, thus excluding the main package from testing but allowing for the fuzzing of internal packages. This organized methodology not only streamlines the testing process but also enhances the focus on discovering vulnerabilities within the code, ultimately leading to more robust software solutions. By continuously refining its support and encouraging community feedback, go-fuzz aims to evolve and adapt to the needs of developers.

What is Google ClusterFuzz?

ClusterFuzz is a comprehensive fuzzing framework aimed at identifying security weaknesses and stability issues within software applications. Used extensively by Google, it serves as the testing backbone for all its products and functions as the fuzzing engine for OSS-Fuzz. This powerful infrastructure comes equipped with numerous features that enable the seamless integration of fuzzing into the software development process. It offers fully automated procedures for filing bugs, triaging them, and resolving issues across various issue tracking platforms. Supporting multiple coverage-guided fuzzing engines, it enhances outcomes through ensemble fuzzing and a range of fuzzing techniques. Moreover, the system provides statistical data to evaluate the effectiveness of fuzzers and track the frequency of crashes. Users benefit from a user-friendly web interface that streamlines the management of fuzzing tasks and crash analysis. ClusterFuzz also accommodates various authentication methods via Firebase, and it boasts functionalities for black-box fuzzing, reducing test cases, and pinpointing regressions through bisection. In conclusion, this powerful tool not only elevates software quality and security but also becomes an essential asset for developers aiming to refine their applications, ultimately leading to more robust and reliable software solutions.

Media

Media

Integrations Supported

Firebase
Honggfuzz
Jira
LibFuzzer
american fuzzy lop

Integrations Supported

Firebase
Honggfuzz
Jira
LibFuzzer
american fuzzy lop

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

dvyukov

Company Website

github.com/dvyukov/go-fuzz

Company Facts

Organization Name

Google

Company Website

github.com/google/clusterfuzz

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Categories and Features

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