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.

Works with

Claude CodeCursorClineWindsurfCodexGooseGitHub CopilotZed

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Install Skill

Run in your terminal

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/performing-fuzzing-with-aflplusplus

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Installation Guide

How to use performing-fuzzing-with-aflplusplus on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add performing-fuzzing-with-aflplusplus
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/performing-fuzzing-with-aflplusplus

Fetches performing-fuzzing-with-aflplusplus from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/performing-fuzzing-with-aflplusplus

Restart Cursor to activate performing-fuzzing-with-aflplusplus. Access via /performing-fuzzing-with-aflplusplus in your agent's command palette.

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

name
performing-fuzzing-with-aflplusplus
description
'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. '
domain
cybersecurity
subdomain
application-security
tags
- fuzzing - aflplusplus - coverage-guided - crash-triage - binary-analysis - security-testing
version
'1.0'
author
mahipal
license
Apache-2.0
nist_ai_rmf
- MEASURE-2.7 - MAP-5.1 - MANAGE-2.4
atlas_techniques
- AML.T0070 - AML.T0066 - AML.T0082
nist_csf
- PR.PS-01 - PR.PS-04 - ID.RA-01 - PR.DS-10

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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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Steps

  1. 1Install skill using provided installation command
  2. 2Test with simple use case relevant to your work
  3. 3Evaluate output quality and relevance
  4. 4Iterate on prompts to improve results
  5. 5Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use when

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid when

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Related Skills

Reviews

4.750 reviews
  • D
    Dhruvi JainDec 16, 2024

    performing-fuzzing-with-aflplusplus has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • O
    Olivia TaylorDec 16, 2024

    performing-fuzzing-with-aflplusplus has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • L
    Luis GhoshDec 8, 2024

    Keeps context tight: performing-fuzzing-with-aflplusplus is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • C
    Charlotte ThomasDec 8, 2024

    performing-fuzzing-with-aflplusplus fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • L
    Liam VermaNov 27, 2024

    Registry listing for performing-fuzzing-with-aflplusplus matched our evaluation — installs cleanly and behaves as described in the markdown.

  • C
    Charlotte VermaNov 27, 2024

    We added performing-fuzzing-with-aflplusplus from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • R
    Rahul SantraNov 15, 2024

    Solid pick for teams standardizing on skills: performing-fuzzing-with-aflplusplus is focused, and the summary matches what you get after install.

  • L
    Liam JohnsonNov 15, 2024

    Solid pick for teams standardizing on skills: performing-fuzzing-with-aflplusplus is focused, and the summary matches what you get after install.

  • O
    OshnikdeepNov 7, 2024

    performing-fuzzing-with-aflplusplus reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • A
    Advait GillNov 7, 2024

    performing-fuzzing-with-aflplusplus reduced setup friction for our internal harness; good balance of opinion and flexibility.

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