performing-fuzzing-with-aflplusplus

Perform coverage-guided fuzzing of compiled binaries using AFL++ (American Fuzzy Lop Plus Plus) to discover memory corruption, crashes, and security vulnerabilities. The tester instruments target binaries with afl-cc/afl-clang-fast, manages input corpora with afl-cmin and afl-tmin, runs parallel fuzzing campaigns with afl-fuzz, and triages crashes using CASR or GDB scripts. Activates for requests involving binary fuzzing, crash discovery, coverage-guided testing, or AFL++ fuzzing campaigns.

4,032 stars

Best use case

performing-fuzzing-with-aflplusplus is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Perform coverage-guided fuzzing of compiled binaries using AFL++ (American Fuzzy Lop Plus Plus) to discover memory corruption, crashes, and security vulnerabilities. The tester instruments target binaries with afl-cc/afl-clang-fast, manages input corpora with afl-cmin and afl-tmin, runs parallel fuzzing campaigns with afl-fuzz, and triages crashes using CASR or GDB scripts. Activates for requests involving binary fuzzing, crash discovery, coverage-guided testing, or AFL++ fuzzing campaigns.

Teams using performing-fuzzing-with-aflplusplus should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/performing-fuzzing-with-aflplusplus/SKILL.md --create-dirs "https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/performing-fuzzing-with-aflplusplus/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/performing-fuzzing-with-aflplusplus/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How performing-fuzzing-with-aflplusplus Compares

Feature / Agentperforming-fuzzing-with-aflplusplusStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Perform coverage-guided fuzzing of compiled binaries using AFL++ (American Fuzzy Lop Plus Plus) to discover memory corruption, crashes, and security vulnerabilities. The tester instruments target binaries with afl-cc/afl-clang-fast, manages input corpora with afl-cmin and afl-tmin, runs parallel fuzzing campaigns with afl-fuzz, and triages crashes using CASR or GDB scripts. Activates for requests involving binary fuzzing, crash discovery, coverage-guided testing, or AFL++ fuzzing campaigns.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Performing Fuzzing with AFL++

## Overview

AFL++ is a community-maintained fork of American Fuzzy Lop (AFL) that provides coverage-guided
fuzzing for compiled binaries. It instruments targets at compile time or via QEMU/Unicorn mode
for binary-only fuzzing, then mutates input corpora to discover new code paths. AFL++ includes
advanced scheduling (MOpt, rare), custom mutators, CMPLOG for input-to-state comparison solving,
and persistent mode for high-throughput fuzzing.


## When to Use

- When conducting security assessments that involve performing fuzzing with aflplusplus
- When following incident response procedures for related security events
- When performing scheduled security testing or auditing activities
- When validating security controls through hands-on testing

## Prerequisites

- AFL++ installed (`apt install afl++` or build from source)
- Target binary source code (for compile-time instrumentation) or QEMU mode for binary-only
- Initial seed corpus of valid inputs for the target format
- Linux system with /proc/sys/kernel/core_pattern configured

## Steps

1. Instrument the target binary with `afl-cc` or `afl-clang-fast`
2. Prepare seed corpus directory with minimal valid inputs
3. Minimize corpus with `afl-cmin` to remove redundant seeds
4. Run `afl-fuzz` with appropriate flags (-i input -o output)
5. Monitor fuzzing progress via afl-whatsup and UI stats
6. Triage crashes with `afl-tmin` minimization and CASR/GDB analysis
7. Report unique crashes with reproduction steps

## Expected Output

```
+++ Findings +++
  unique crashes: 12
  unique hangs: 3
  last crash: 00:02:15 ago
+++ Coverage +++
  map density: 4.23% / 8.41%
  paths found: 1847
  exec speed: 2145/sec
```

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