GitHub - dvyukov/go-fuzz: Randomized testing for Go

Matt Layher - mdlayher.com

Go 1.18 is coming out soon. It's a huge release, but native fuzzing has a special place in my heart. Not much has been written yet on how Go's fuzzing system actually works, so I'll talk a bit about that here.

Go is one of the most prominent general-purpose programming languages nowadays. Google, Apple, Microsoft, Amazon, and Adobe, to name a few, have been using the language extensively. It’s the language of choice behind multiple cloud computing projects such as Kubernetes, and it’s steadily expanding towards numerous areas of software development. In this article, you'll find resources to learn about Go and its ecosystem.

Last Friday was my last day at Google. This article is a reflection on the last seven years of my life, thinking about what was important and what I'll do differently in the future.

When we switched to a new search query parser in September 2020, you'd never know that anything had changed. This is an account of the rigorous testing that happened behind the scenes to ensure a seamless transition.

Fuzzing is a testing technique with randomized inputs that is used to find problematic edge cas [...]

Go-Fuzz is like AFL but for Go. If you have a Go package that parses some input, you might be able fuzz it with Go-Fuzz (terms and conditions apply). Not everything can be fuzzed very easily. For example Go-Fuzz does not like cycling imports, so if one of your sub-packages imports the main package then you are in trouble (I am looking at your Chroma). The rest of the article will show how to use Go-Fuzz to fuzz a Go library named iprange at: https://github.com/malfunkt/iprange Code and fuzzing artifacts are at: https://github.com/parsiya/Go-Security/tree/master/go-fuzz/iprange

I previously wrote about starting a Go project in 2018. A lot has changed since I wrote that and I had been wanting to write an updated version. What follows should be enough for anyone new to Go to …

Curated list of resources on testing distributed systems

A revolutionary coverage-driven fuzzer credited with finding countless vulnerabilities in open-source code.