Ffuf Web Fuzzing

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:CUSTOM then use CUSTOM instead of FUZZ

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

4. POST Data Fuzzing

# Basic POST fuzzing
ffuf -w /path/to/passwords.txt -X POST -d "username=admin&password=FUZZ" -u https://target.com/login.php -fc 401

# JSON POST data
ffuf -w entries.txt -u https://target.com/api -X POST -H "Content-Type: application/json" -d '{"name": "FUZZ", "key": "value"}' -fr "error"

# Fuzzing multiple POST fields
ffuf -w users.txt:USER -w passes.txt:PASS -X POST -d "username=USER&password=PASS" -u https://target.com/login -mode pitchfork

5. Header Fuzzing

# Custom headers
ffuf -w /path/to/wordlist.txt -u https://target.com -H "X-Custom-Header: FUZZ"

# Multiple headers
ffuf -w /path/to/wordlist.txt -u https://target.com -H "User-Agent: FUZZ" -H "X-Forwarded-For: 127.0.0.1"

Filtering and Matching

Matchers (Include Results)

• -mc: Match status codes (default: 200-299,301,302,307,401,403,405,500)
• -ml: Match line count
• -mr: Match regex
• -ms: Match response size
• -mt: Match response time (e.g., >100 or `"

Command injection

ffuf -w cmdi_payloads.txt -u https://target.com/execute?cmd=FUZZ -fr "error"

### Batch Processing Multiple Targets
```bash
# Process multiple URLs
cat targets.txt | xargs -I@ sh -c 'ffuf -w wordlist.txt -u @/FUZZ -ac'

# Loop through multiple targets with results
for url in $(cat targets.txt); do 
    ffuf -w wordlist.txt -u $url/FUZZ -ac -o "results_$(echo $url | md5sum | cut -d' ' -f1).json"
done

Best Practices

1. ALWAYS Use Auto-Calibration

Use -ac by default for every scan. This is non-negotiable for productive pentesting:

ffuf -w wordlist.txt -u https://target.com/FUZZ -ac

2. Use Raw Requests for Authentication

Don't struggle with command-line flags for complex auth. Capture the full request and use --request:

# 1. Capture authenticated request from Burp/DevTools
# 2. Save to req.txt with FUZZ keyword in place
# 3. Run with -ac
ffuf --request req.txt -w wordlist.txt -ac -o results.json

3. Use Appropriate Wordlists

• Directory discovery: SecLists Discovery/Web-Content (raft-large-directories.txt, directory-list-2.3-medium.txt)
• Subdomains: SecLists Discovery/DNS (subdomains-top1million-5000.txt)
• Parameters: SecLists Discovery/Web-Content (burp-parameter-names.txt)
• Usernames: SecLists Usernames
• Passwords: SecLists Passwords
• Source: https://github.com/danielmiessler/SecLists

3. Rate Limiting for Stealth

Use -rate to avoid triggering WAF/IDS or overwhelming the server:

ffuf -w wordlist.txt -u https://target.com/FUZZ -rate 2 -t 10

4. Filter Strategically

• Check the default response first to identify common response sizes, status codes, or patterns
• Use -fs to filter by size or -fc to filter by status code
• Combine filters: -fc 403,404 -fs 1234

5. Save Results Appropriately

Always save results to a file for later analysis:

ffuf -w wordlist.txt -u https://target.com/FUZZ -o results.json -of json

6. Use Interactive Mode

Press ENTER during execution to drop into interactive mode where you can:

• Adjust filters on the fly
• Save current results
• Restart the scan
• Manage the queue

7. Recursion Depth

Be careful with recursion depth to avoid getting stuck in infinite loops or overwhelming the server:

ffuf -w wordlist.txt -u https://target.com/FUZZ -recursion -recursion-depth 2 -maxtime-job 120

Common Patterns and One-Liners

Quick Directory Scan

ffuf -w ~/wordlists/common.txt -u https://target.com/FUZZ -mc 200,301,302,403 -ac -c -v

Comprehensive Scan with Extensions

ffuf -w ~/wordlists/raft-large-directories.txt -u https://target.com/FUZZ -e .php,.html,.txt,.bak,.old -ac -c -v -o results.json

Authenticated Fuzzing (Raw Request)

# 1. Save your authenticated request to req.txt with FUZZ keyword
# 2. Run:
ffuf --request req.txt -w ~/wordlists/api-endpoints.txt -ac -o results.json -of json

API Endpoint Discovery

ffuf -w ~/wordlists/api-endpoints.txt -u https://api.target.com/v1/FUZZ -H "Authorization: Bearer TOKEN" -mc 200,201 -ac -c

Subdomain Discovery with Auto-Calibration

ffuf -w ~/wordlists/subdomains-top5000.txt -u https://FUZZ.target.com -ac -c -v

POST Login Brute Force

ffuf -w ~/wordlists/passwords.txt -X POST -d "username=admin&password=FUZZ" -u https://target.com/login -fc 401 -rate 5 -ac

IDOR Testing with Auth

# Use req.txt with authenticated headers and FUZZ in the ID parameter
ffuf --request req.txt -w numbers.txt -ac -mc 200 -fw 100-200

Configuration File

Create ~/.config/ffuf/ffufrc for default settings:

[http]
headers = ["User-Agent: Mozilla/5.0"]
timeout = 10

[general]
colors = true
threads = 40

[matcher]
status = "200-299,301,302,307,401,403,405,500"

Troubleshooting

Too Many False Positives

• Use -ac for auto-calibration
• Check default response and filter by size with -fs
• Use regex filtering with -fr

Too Slow

• Increase threads: -t 100
• Reduce wordlist size
• Use -ignore-body if you don't need response content

Getting Blocked

• Reduce rate: -rate 2
• Add delays: -p 0.5-1.5
• Reduce threads: -t 10
• Randomize User-Agent
• Use proxy rotation

Missing Results

• Check if you're filtering too aggressively
• Use -mc all to see all responses
• Disable auto-calibration temporarily
• Use verbose mode -v to see what's happening

Resources

• Official GitHub: https://github.com/ffuf/ffuf
• Wiki: https://github.com/ffuf/ffuf/wiki
• Codingo's Guide: https://codingo.io/tools/ffuf/bounty/2020/09/17/everything-you-need-to-know-about-ffuf.html
• Practice Lab: http://ffuf.me
• SecLists Wordlists: https://github.com/danielmiessler/SecLists

Quick Reference Card

| Task | Command Template | |------|------------------| | Directory Discovery | ffuf -w wordlist.txt -u https://target.com/FUZZ -ac | | Subdomain Discovery | ffuf -w subdomains.txt -u https://FUZZ.target.com -ac | | Parameter Fuzzing | ffuf -w params.txt -u https://target.com/page?FUZZ=value -ac | | POST Data Fuzzing | ffuf -w wordlist.txt -X POST -d "param=FUZZ" -u https://target.com/endpoint | | With Extensions | Add -e .php,.html,.txt | | Filter Status | Add -fc 404,403 | | Filter Size | Add -fs 1234 | | Rate Limit | Add -rate 2 | | Save Output | Add -o results.json | | Verbose | Add -c -v | | Recursion | Add -recursion -recursion-depth 2 | | Through Proxy | Add -x http://127.0.0.1:8080 |

Additional Resources

This skill includes supplementary materials in the resources/ directory:

Resource Files

• WORDLISTS.md: Comprehensive guide to SecLists wordlists, recommended lists for different scenarios, file extensions, and quick reference patterns
• REQUEST_TEMPLATES.md: Pre-built req.txt templates for common authentication scenarios (JWT, OAuth, session cookies, API keys, etc.) with usage examples

Helper Script

• ffuf_helper.py: Python script to assist with:
• Analyzing ffuf JSON results for anomalies and interesting findings
• Creating req.txt template files from command-line arguments
• Generating number-based wordlists for IDOR testing

Helper Script Usage:

# Analyze results to find interesting anomalies
python3 ffuf_helper.py analyze results.json

# Create authenticated request template
python3 ffuf_helper.py create-req -o req.txt -m POST -u "https://api.target.com/users" \
    -H "Authorization: Bearer TOKEN" -d '{"action":"FUZZ"}'

# Generate IDOR testing wordlist
python3 ffuf_helper.py wordlist -o ids.txt -t numbers -s 1 -e 10000

When to use resources:

• Users need wordlist recommendations → Reference WORDLISTS.md
• Users need help with authenticated requests → Reference REQUEST_TEMPLATES.md
• Users want to analyze results → Use ffuf_helper.py analyze
• Users need to generate req.txt → Use ffuf_helper.py create-req
• Users need number ranges for IDOR → Use ffuf_helper.py wordlist

Notes for Claude

When helping users with ffuf:

1. ALWAYS include -ac in every command - This is mandatory for productive pentesting and result analysis
2. When users mention authenticated fuzzing or provide auth tokens/cookies:

• Suggest creating a req.txt file with the full HTTP request
• Show them how to insert FUZZ where they want to fuzz
• Use ffuf --request req.txt -w wordlist.txt -ac

1. Always recommend starting with -ac for auto-calibration
2. Suggest appropriate wordlists from SecLists based on the task
3. Remind users to use rate limiting (-rate) for production targets
4. Encourage saving output to files for documentation: -o results.json
5. Suggest filtering strategies based on initial reconnaissance
6. Always use the FUZZ keyword (case-sensitive)
7. Consider stealth: lower threads, rate limiting, and delays for sensitive targets
8. For pentesting reports, use -of html or -of csv for client-friendly formats
9. When analyzing ffuf results for users:

• Assume they used -ac (if not, results will be too noisy)
• Focus on anomalies: different status codes, response sizes, timing
• Look for interesting endpoints: admin, api, backup, config, .git, etc.
• Flag potential vulnerabilities: error messages, stack traces, version info
• Suggest follow-up fuzzing on interesting findings

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: CarbeneAI
• Source: CarbeneAI/Forge
• License: MIT
• Homepage: http://carbene.ai/open-source

Install and usage instructions live in the source repository linked above.