offensive-fuzzing

offensive-fuzzing is a skill for Claude Code, Codex from SnailSploit/Claude-Red. It costs 91 tokens per session (3,545 once invoked), scanned A, original, MIT.

A guide to fuzzing, a method that sends many automatically modified inputs to software to uncover crashes and other bugs. It covers choosing a fuzzer, preparing test code and sample inputs, measuring coverage, and reviewing crashes.

In plain words
What is it for?
Selecting AFL++, libFuzzer, Honggfuzz, Boofuzz, syzkaller, or related tools; writing test harnesses; building and instrumenting targets; running campaigns; and triaging results.
Why use it?
It provides a repeatable process for finding problems in parsers, network interfaces, system calls, and other input-handling code.

Skill for Claude CodeCodex

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

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is ../honggfuzz/honggfuzz -i sync_dir/fuzzer1/queue -W sync_dir/hfuzz \.

Good fit Selecting AFL++, libFuzzer, Honggfuzz, Boofuzz, syzkaller, or related tools; writing test harnesses; building and instrumenting targets; running campaigns; and triaging results.

Compare 6 skills from other repositories ↓
About the project

claude-red is a library of structured skills that give Claude specialized offensive-security methods for areas such as web vulnerabilities, shellcode, exploit development, and identity systems. It is intended for authorized red-team work, bug-bounty triage, security research, CTF preparation, and operator training. Its catalogue contains the project's skills for loading these security specializations into Claude.

SnailSploit/Claude-Red · 7,709 stars · on GitHub

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/SnailSploit/Claude-Red
agentmods
npx agentmods add skills/snailsploit/claude-red/offensive-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 offensive-fuzzing

README.md
[![agentmods](https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-fuzzing/github.svg)](https://agentmods.dev/skills/snailsploit/claude-red/offensive-fuzzing)
Your own site
<a href="https://agentmods.dev/skills/snailsploit/claude-red/offensive-fuzzing"><img src="https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-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 offensive-fuzzing

Your own site · 80×15
<a href="https://agentmods.dev/skills/snailsploit/claude-red/offensive-fuzzing"><img src="https://agentmods.dev/badge/skills/snailsploit/claude-red/offensive-fuzzing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 91 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,545 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
  • 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 $0.00091 $0.03545
Opus 5.5 $0.00036 $0.01418
Sonnet 5.5 $0.00018 $0.00709
Haiku 4.5 $0.00009 $0.00354

Measured 1mo ago against content hash fcd129b42cdf, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

offensive-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 1mo 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

Skills/fuzzing/offensive-fuzzing/SKILL.md · 339 lines

How it starts

The opening of the file, as written. The whole thing — 339 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Offensive Fuzzing

Fuzzer Types

Type Coverage Speed Tools
BlackBox Poor Fast Peach, Boofuzz
GreyBox Good Fast AFL++, Honggfuzz, libFuzzer, WinAFL
Snapshot Good Fastest Nyx, wtf, Snapchange
WhiteBox Best Slow KLEE, QSYM, SymSan
Ensemble Best Fast AFL++ + Honggfuzz + libFuzzer

GreyBox sub-variants: Directed (AFLGo, UAFuzz), Grammar (AFLSmart, Tlspuffin), Concolic (QSYM, Driller), Kernel (syzkaller, kAFL, wtf).

Core Workflow

Research target → Choose analyses → Build harness → Seed corpus → Instrument → Fuzz → Triage crashes → Report

1. Research Target

  • Map all input surfaces (files, network, IPC, syscalls, IOCTL)
  • Identify high-value areas: previously patched code, complex parsers, newly added code, input ingestion points
  • For kernel modules: look beyond copy_from_user — DMA-BUF ops, page fault handlers, VM operation structs, allocation callbacks

2. Instrument and Build

# AFL++ (preferred for GreyBox)
CC=afl-clang-fast CXX=afl-clang-fast++ cmake -DCMAKE_BUILD_TYPE=Release .. && make -j

# libFuzzer + ASan/UBSan (C/C++)
cmake -DCMAKE_CXX_FLAGS="-fsanitize=fuzzer,address,undefined -O1 -g" ..

# CmpLog build for hard compares
AFL_LLVM_CMPLOG=1 CC=afl-clang-fast CXX=afl-clang-fast++ make clean all

Windows (MSVC): Project Properties → C/C++ → Address Sanitizer: Yes (/fsanitize=address)

3. Write Harness

libFuzzer (C++):

#include <cstdint>
#include <cstddef>
extern "C" int LLVMFuzzerTestOneInput(const uint8_t* data, size_t size) {
    parse_or_process(data, size);
    return 0;
}

Honggfuzz HF_ITER (persistent mode — preferred for large targets):

#include "honggfuzz.h"
int main(int argc, char** argv) {
    initialize_target(); // runs once
    for (;;) {
        size_t len; uint8_t *buf;
        HF_ITER(&buf, &len);
        FILE* s = fmemopen(buf, len, "r");
        target_function(s);
        fclose(s);
        reset_target_state();
    }
}

Read the full file on GitHub · 339 lines

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. 1mo ago First seen · 339 lines · 91 tokens per session scan A fcd129b42cdf

Subscribe to this mod's changes

offensive-fuzzing is a skill published in the GitHub repository SnailSploit/Claude-Red (7,709 stars, last pushed 9d ago), licensed MIT. It adds 91 tokens to every session and 3,545 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-30.

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