Does this skill support memory sanitizers?

Yes, it provides optimized configuration patterns for integrating AddressSanitizer (ASan) and UndefinedBehaviorSanitizer (UBSan) to detect non-crashing memory errors.

Is it better to run AFL++ on a host machine or via Docker?

While Docker provides environment consistency and easy setup, the skill supports both. For maximum performance, running on a dedicated host or VM with optimized kernel settings is recommended.

When should I use AFL++ instead of libFuzzer?

Choose AFL++ for mature projects where you need to maximize execution speed through parallelization or when libFuzzer coverage has plateaued.

What is the primary advantage of AFL++ over other fuzzers?

AFL++ offers superior performance and features compared to the original AFL, including stable multi-core support, more diverse mutation strategies, and a wide array of instrumentation modes like LTO.

AFL++ Security Fuzzer

Name: AFL++ Security Fuzzer
Author: trailofbits

bytrailofbits

•

938

보안 및 테스팅

Automates high-performance multi-core fuzzing for C/C++ projects to detect security vulnerabilities and memory corruption issues.

소개

The aflpp skill integrates the advanced AFL++ fuzzer into the Claude Code environment, providing domain-specific guidance for security researchers and C/C++ developers. It streamlines the setup of parallelized fuzzing campaigns, offering optimized compilation strategies and best practices for writing effective harnesses. By leveraging AFL++'s superior mutation engines and multi-core support, this skill helps users achieve deeper code coverage and identify complex bugs that standard unit testing might miss.

주요 기능

Multi-core fuzzing orchestration for maximum throughput
Optimized compilation modes including LTO, LLVM, and GCC
Integrated AddressSanitizer (ASan) and UBSan support
938 GitHub stars
Standardized templates for libFuzzer-style harnesses
Automated corpus management and minimization workflows

사용 사례

Finding memory safety vulnerabilities in complex C/C++ libraries
Conducting deep security audits of production-grade software
Scaling fuzzing campaigns across multiple CPU cores for faster discovery

소개

주요 기능

Multi-core fuzzing orchestration for maximum throughput
Optimized compilation modes including LTO, LLVM, and GCC
Integrated AddressSanitizer (ASan) and UBSan support
938 GitHub stars
Standardized templates for libFuzzer-style harnesses
Automated corpus management and minimization workflows

사용 사례

Finding memory safety vulnerabilities in complex C/C++ libraries
Conducting deep security audits of production-grade software
Scaling fuzzing campaigns across multiple CPU cores for faster discovery