aflpp

Automate fuzz testing of C/C++ codebases with AFL++ across multiple cores.

Updated Jul 10, 2025
One-click install
npx skills add https://github.com/Superlend/superloop-core-contracts --skill aflpp
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: aflpp
Source: https://github.com/Superlend/superloop-core-contracts/tree/main/.cursor/skills/testing-handbook-skills/skills/aflpp
Command: npx skills add https://github.com/Superlend/superloop-core-contracts --skill aflpp

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AFL++ accelerates the discovery of bugs in C/C++ projects by enabling large-scale, multi-core fuzzing campaigns that quickly explore diverse inputs.

Core Features & Use Cases

  • Scalable Fuzzing: Parallel fuzz campaigns across multiple cores for high-throughput bug finding.
  • Advanced Mutation Strategies: Rich mutation operators and persistent mode for deeper coverage.
  • Use Case: Fuzz a large C/C++ library to uncover memory corruption or logic errors across complex input formats.

Quick Start

Install AFL++ and set up a sample fuzzing target. Build with the AFL++ clang-based toolchain and run a fuzz campaign to start collecting crashes and coverage data.

Frequently Asked Questions about aflpp

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up multi-core fuzzing for a C/C++ codebase?

Yes, AFL++ supports scalable fuzzing campaigns across multiple cores to maximize throughput. It leverages rich mutation operators and LLVM-based instrumentation to quickly explore diverse inputs and uncover memory corruption or logic errors.

What is AFL++ used for in security testing?

AFL++ is used in security testing to automate fuzz testing of C/C++ codebases. It accelerates the discovery of bugs by applying advanced mutation strategies and persistent mode for deeper code coverage across complex input formats.

Do I need LLVM instrumentation to run an AFL++ fuzz campaign?

To start an AFL++ fuzz campaign, install AFL++ and set up a sample fuzzing target. Build the target with the AFL++ clang-based toolchain, configure multi-core fuzzing options, and run the campaign to start collecting crashes and coverage data.

Does AFL++ support persistent mode for complex input formats?

AFL++ distinguishes itself through multi-core parallel fuzzing campaigns and advanced mutation strategies. This scalable approach enables high-throughput bug discovery and rapid exploration of diverse inputs compared to single-core fuzzing setups.