fuzzing

fuzzing is a skill for Claude Code, Codex from mohitmishra786/low-level-dev-skills. It costs 93 tokens per session (2,371 once invoked), scanned A, original, MIT.

A guide to fuzzing, which tests software by feeding it many generated or altered inputs. It focuses on C and C++ fuzz targets, crash reproduction, coverage, sanitizers, and CI.

In plain words
What is it for?
Use it to fuzz parsers and input boundaries with libFuzzer or AFL++, maintain test inputs, reproduce failures, and run fuzzing with sanitizers.
Why use it?
It helps uncover crashes and unexpected input-handling bugs that ordinary test cases may miss.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python infra/helper.py build_image yourproject.

not rated 203repo +8 2mo ago A scan Socket: passSnyk: passSkillSpector: pass 93 tokens original MIT

Good fit Use it to fuzz parsers and input boundaries with libFuzzer or AFL++, maintain test inputs, reproduce failures, and run fuzzing with sanitizers.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/mohitmishra786/low-level-dev-skills
agentmods
npx agentmods add skills/mohitmishra786/low-level-dev-skills/fuzzing

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for fuzzing

README.md
[![agentmods](https://agentmods.dev/badge/skills/mohitmishra786/low-level-dev-skills/fuzzing/github.svg)](https://agentmods.dev/skills/mohitmishra786/low-level-dev-skills/fuzzing)
Your own site
<a href="https://agentmods.dev/skills/mohitmishra786/low-level-dev-skills/fuzzing"><img src="https://agentmods.dev/badge/skills/mohitmishra786/low-level-dev-skills/fuzzing/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for fuzzing

Your own site · 80×15
<a href="https://agentmods.dev/skills/mohitmishra786/low-level-dev-skills/fuzzing"><img src="https://agentmods.dev/badge/skills/mohitmishra786/low-level-dev-skills/fuzzing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,371 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 18 Mar 2026
  • Snyk pass 21 Feb 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00093 $0.02371
Opus 5 $0.00046 $0.01185
Sonnet 5 $0.00019 $0.00474
Haiku 4.5 $0.00009 $0.00237

Measured 9d ago against content hash 9693fdd9c32d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

fuzzing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/runtimes/fuzzing/SKILL.md · 318 lines

How it starts

The opening of the file, as written. The whole thing — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fuzzing

Purpose

Guide agents through setting up and running coverage-guided fuzz testing: libFuzzer (in-process) and AFL++ (fork-based), with sanitizer integration and CI pipeline setup.

Triggers

  • "How do I fuzz-test my parser/deserializer?"
  • "What is a fuzz target / how do I write one?"
  • "How do I set up libFuzzer?"
  • "How do I use AFL++ on my program?"
  • "How do I run fuzzing in CI?"
  • "Fuzzer found a crash — how do I reproduce it?"

Workflow

1. Write a fuzz target (libFuzzer)

A fuzz target is a function that accepts arbitrary bytes and exercises the code under test.

// fuzz_parser.c
#include <stdint.h>
#include <stddef.h>
#include "myparser.h"

// Entry point called by libFuzzer with random data
int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    // Must not abort/exit on invalid input (that's expected)
    // Must not read outside [data, data+size)

    MyParser *p = parser_create();
    if (p) {
        parser_feed(p, (const char *)data, size);
        parser_destroy(p);
    }
    return 0;  // Always return 0 (non-zero means discard input)
}

Key rules:

  • Never call abort(), exit(), or use global state that persists across calls
  • Handle all inputs gracefully (crash = bug found)
  • Keep the target fast: the fuzzer calls it millions of times

2. Build with libFuzzer

# Clang (libFuzzer is built into Clang)
clang -fsanitize=fuzzer,address -g -O1 \
    fuzz_parser.c myparser.c -o fuzz_parser

# With UBSan too
clang -fsanitize=fuzzer,address,undefined -g -O1 \
    fuzz_parser.c myparser.c -o fuzz_parser

-fsanitize=fuzzer links libFuzzer and provides main(). Do not provide your own main() in the fuzz target.

3. Run libFuzzer

# Create corpus directory
mkdir -p corpus

# Seed with known-good inputs (greatly accelerates coverage)
cp tests/inputs/* corpus/

# Run the fuzzer
./fuzz_parser corpus/ -max_len=65536 -timeout=10

# Run for a time limit
./fuzz_parser corpus/ -max_total_time=3600

# Run with specific number of jobs (parallel)
./fuzz_parser corpus/ -jobs=4 -workers=4

# Minimise a corpus (remove redundant inputs)
./fuzz_parser -merge=1 corpus_min/ corpus/

Read the full file on GitHub · 318 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 318 lines · 93 tokens per session scan A 9693fdd9c32d

Subscribe to this mod's changes

fuzzing is a skill published in the GitHub repository mohitmishra786/low-level-dev-skills (203 stars, last pushed 2mo ago), licensed MIT. It adds 93 tokens to every session and 2,371 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

synthetic-monitoring

AI-powered synthetic monitoring skill for e-commerce websites. Designs automated user journey tests for add-to-cart, checkout, and payment flows with alerting rules and performance baselines.

nexscope-ai/eCommerce-Skills · 0 tokens

visual-regression-testing

AI-powered visual regression testing skill for e-commerce websites. Designs screenshot comparison workflows, mobile/desktop visual checks, and change detection alerts to prevent conversion-killing UI bugs.

nexscope-ai/eCommerce-Skills · 0 tokens

shopify-ab-testing

Run data-driven A/B tests on your Shopify store. Test product pages, pricing, images, copy, checkout flow, and marketing campaigns with proper statistical methodology.

nexscope-ai/eCommerce-Skills · 0 tokens

accessibility-testing

Audit web interfaces against WCAG 2.1 AA/AAA standards, identify violations, and produce actionable remediation reports with code fixes. Use when the user requests accessibility testing or provides relevant inputs for this workflow.

seb1n/awesome-ai-agent-skills · 46 tokens

testing

Generate, execute, and analyze tests for codebases, covering unit, integration, and end-to-end testing with coverage reporting. Use when the user requests testing or provides relevant inputs for this workflow.

seb1n/awesome-ai-agent-skills · 41 tokens

playwright

Browser automation, web scraping, E2E testing, and visual regression with Playwright. Covers 30+ patterns: login flows, form testing, responsive design checks, broken link validation, API mocking, data extraction, PDF generation, accessibility audits (axe-core), performance budgets (Lighthouse), visual diffing…

EliasOulkadi/shokunin · 0 tokens