Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add CarbeneAI/Forge --skill ffufgit clone --depth 1 https://github.com/CarbeneAI/ForgeWrote 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.
[](https://agentmods.dev/skills/carbeneai/forge/ffuf)<a href="https://agentmods.dev/skills/carbeneai/forge/ffuf"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/ffuf/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.
<a href="https://agentmods.dev/skills/carbeneai/forge/ffuf"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/ffuf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00034 | $0.04997 |
| Opus 5.5 | $0.00014 | $0.01999 |
| Sonnet 5.5 | $0.00007 | $0.00999 |
| Haiku 4.5 | $0.00003 | $0.00500 |
Grade A, and why
ffuf-web-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.
This is a copy
100% identical to ffuf-web-fuzzing — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 502 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FFUF (Fuzz Faster U Fool) Skill
Contributed by: Joseph Thacker (@rez0)
Overview
FFUF is a fast web fuzzer written in Go, designed for discovering hidden content, directories, files, subdomains, and testing for vulnerabilities during penetration testing. It's significantly faster than traditional tools like dirb or dirbuster.
Installation
# Using Go
go install github.com/ffuf/ffuf/v2@latest
# Using Homebrew (macOS)
brew install ffuf
# Binary download
# Download from: https://github.com/ffuf/ffuf/releases/latest
Core Concepts
The FUZZ Keyword
The FUZZ keyword is used as a placeholder that gets replaced with entries from your wordlist. You can place it anywhere:
- URLs:
https://target.com/FUZZ - Headers:
-H "Host: FUZZ" - POST data:
-d "username=admin&password=FUZZ" - Multiple locations with custom keywords:
-w wordlist.txt:CUSTOMthen useCUSTOMinstead ofFUZZ
Multi-wordlist Modes
- clusterbomb: Tests all combinations (default) - cartesian product
- pitchfork: Iterates through wordlists in parallel (1-to-1 matching)
- sniper: Tests one position at a time (for multiple FUZZ positions)
Common Use Cases
1. Directory and File Discovery
# Basic directory fuzzing
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ
# With file extensions
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -e .php,.html,.txt,.pdf
# Colored and verbose output
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -c -v
# With recursion (finds nested directories)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -recursion -recursion-depth 2
2. Subdomain Enumeration
# Virtual host discovery
ffuf -w /path/to/subdomains.txt -u https://target.com -H "Host: FUZZ.target.com" -fs 4242
# Note: -fs 4242 filters out responses of size 4242 (adjust based on default response size)
3. Parameter Fuzzing
# GET parameter names
ffuf -w /path/to/params.txt -u https://target.com/script.php?FUZZ=test_value -fs 4242
# GET parameter values
ffuf -w /path/to/values.txt -u https://target.com/script.php?id=FUZZ -fc 401
# Multiple parameters
ffuf -w params.txt:PARAM -w values.txt:VAL -u https://target.com/?PARAM=VAL -mode clusterbomb
What ships with it
3 files 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.
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.
- 1mo ago First seen · 502 lines · 34 tokens per session scan A 6765af5f46f7
ffuf-web-fuzzing is a skill published in the GitHub repository CarbeneAI/Forge (9 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 4,997 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to ffuf-web-fuzzing, differing in 0 lines, and is treated as a copy.
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