codeql

CodeQL This open source repository contains the standard CodeQL libraries and queries that power GitHub Advanced Security and the other application security products that GitHub makes available to its customers worldwide. How do I learn CodeQL and run queries? There is extensive documentation abo...

test-fuzz

test-fuzz test-fuzz is a Cargo subcommand and a collection of Rust macros to automate certain tasks related to fuzzing with afl.rs, including: generating a fuzzing corpus implementing a fuzzing harness test-fuzz accomplishes these in part using Rust's testing facilities. For example, to generate ...

autoharness

AutoHarness Created by Akshat Parikh What is this tool? AutoHarness is a tool that automatically generates fuzzing harnesses for you. This idea stems from a concurrent problem in fuzzing codebases today: large codebases have thousands of functions and pieces of code that can be embedded fairly de...

tmux-fuzzing

Fuzzing Lab: Enhancing Fuzzing for tmux Software Security @ EPFL, Spring 2025 Abstract In this lab, we enhanced the fuzzing efforts for the tmux terminal multiplexer within Google's OSS-Fuzz infrastructure. We first established a baseline by evaluating the line coverage of the existing input-fuzz...

toothpicker

ToothPicker ToothPicker is an in-process, coverage-guided fuzzer for iOS. It was developed to specifically targets iOS's Bluetooth daemon bluetoothd and to analyze various Bluetooth protocols on iOS. As it is built using FRIDA, it can be adapted to target any platform that runs FRIDA. This...

OpenEXR Makes Use of Uninitialized Memory

SummaryWhile fuzzing openexrexrcheckfuzzer, Valgrind reports a conditional branch depending on uninitialized data inside genericunpack. This indicates a use of uninitialized memory CWE-457. The issue is reproducible with the current OSS-Fuzz harness and a single-file PoC. DetailsEnvironment:-...

Coverage-Guided Multi-Agent Harness Generation for Java Library Fuzzing

Coverage-guided fuzzing has proven effective for software testing, but targeting library code requires specialized fuzz harnesses that translate fuzzer-generated inputs into valid API invocations. Manual harness creation is time-consuming and requires deep understanding of API semantics,...