fuzz

Generate context-aware fuzz test inputs targeting input parsing code vulnerabilities.

12|1|Updated Feb 9, 2026
One-click install
npx skills add https://github.com/florianbuetow/claude-code --skill fuzz-florianbuetow
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: fuzz
Source: https://github.com/florianbuetow/claude-code/tree/main/plugins/appsec/skills/fuzz
Command: npx skills add https://github.com/florianbuetow/claude-code --skill fuzz-florianbuetow

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the generation of intelligent, context-aware fuzz test inputs to uncover vulnerabilities in input parsing and processing code.

Core Features & Use Cases

  • Context-Aware Input Generation: Analyzes code to create tailored fuzz inputs (boundary values, type confusion, encoding edge cases, injection payloads).
  • Multi-Depth Analysis: Supports quick, standard, deep, and expert fuzzing depths for varying levels of testing rigor.
  • Use Case: When developing an API endpoint that accepts user-uploaded files, use this Skill to generate a comprehensive set of malicious or malformed file inputs to test the API's resilience against various attacks like path traversal or content-type manipulation.

Quick Start

Use the fuzz skill to generate deep fuzz inputs for the 'email' input field in 'src/api/users.ts'.

Frequently Asked Questions about fuzz

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

FAQPage Schema
How do I generate fuzz test inputs for API endpoints and file parsers?

To generate fuzz test inputs for API endpoints and file parsers, analyze the input parsing code to produce context-aware payloads like boundary values, type confusion, and encoding edge cases. The process yields structured JSON test case sets for integration with test harnesses.

What is context-aware fuzzing for security testing?

Context-aware fuzzing for security testing is a vulnerability discovery method that analyzes input parsing code to generate tailored malicious payloads. It targets specific input handlers like CLI arguments with boundary values and injection payloads rather than random data generation.

Can I use automated payload generation for path traversal and content-type manipulation testing?

Yes, you can use automated payload generation for path traversal and content-type manipulation testing. By analyzing input parsing code, the generation creates tailored malformed file inputs to test API resilience against specific security vulnerabilities.

Does fuzzing depth affect the test case sets produced for input validation?

Yes, fuzzing depth affects the test case sets produced for input validation. You can select quick, standard, deep, or expert fuzzing depths to vary the testing rigor and the comprehensiveness of the generated boundary values and injection payloads.

What's the best way to integrate generated fuzz inputs into an existing test harness?

The best way to integrate generated fuzz inputs into an existing test harness is to utilize the structured JSON test case sets produced by the input analysis. These JSON sets containing context-specific injection payloads can be parsed and passed to test harnesses.