ffuf-web-fuzzing（ffuf 网络模糊测试）

FFUF (Fuzz Faster U Fool) Skill

When to Use

• You are fuzzing web targets with ffuf during authorized security testing or penetration testing.
• The task involves content discovery, subdomain enumeration, parameter fuzzing, or authenticated request fuzzing.
• You need guidance on wordlists, filtering, calibration, and interpreting ffuf results efficiently.

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 <100 milliseconds)
• -mw: Match word count

Filters (Exclude Results)

• -fc: Filter status codes (e.g., -fc 404,403,401)
• -fl: Filter line count
• -fr: Filter regex (e.g., -fr "error")
• -fs: Filter response size (e.g., -fs 42,4242)
• -ft: Filter response time
• -fw: Filter word count

Auto-Calibration (USE BY DEFAULT!)

CRITICAL: Always use -ac unless you have a specific reason not to. This is especially important when having Claude analyze results, as it dramatically reduces noise and false positives.

# Auto-calibration - ALWAYS USE THIS
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -ac

# Per-host auto-calibration (useful for multiple hosts)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -ach

# Custom auto-calibration string (for specific patterns)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -acc "404NotFound"

Why -ac is essential:

• Automatically detects and filters repetitive false positive responses
• Removes noise from dynamic websites with random content
• Makes results analysis much easier for both humans and Claude
• Prevents thousands of identical 404/403 responses from cluttering output
• Adapts to the target's specific behavior

When Claude analyzes your ffuf results, -ac is MANDATORY - without it, Claude will waste time sifting through thousands of false positives instead of finding the interesting anomalies.

Rate Limiting and Timing

Rate Control

# Limit to 2 requests per second (stealth mode)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -rate 2

# Add delay between requests (0.1 to 2 seconds random)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -p 0.1-2.0

# Set number of concurrent threads (default: 40)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -t 10

Time Limits

# Maximum total execution time (60 seconds)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -maxtime 60

# Maximum time per job (useful with recursion)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -maxtime-job 60 -recursion

Output Options

Output Formats

# JSON output
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -o results.json

# HTML output
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -of html -o results.html

# CSV output
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -of csv -o results.csv

# All formats
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -of all -o results

# Silent mode (no progress, only results)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -s

# Pipe to file with tee
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -s | tee results.txt

Advanced Techniques

Using Raw HTTP Requests (Critical for Authenticated Fuzzing)

This is one of the most powerful features of ffuf, especially for authenticated requests with complex headers, cookies, or tokens.

Workflow:

1. Capture a full authenticated request (from Burp Suite, browser DevTools, etc.)
2. Save it to a file (e.g., req.txt)
3. Replace the value you want to fuzz with the FUZZ keyword
4. Use the --request flag

# From a file containing raw HTTP request
ffuf --request req.txt -w /path/to/wordlist.txt -ac

Example req.txt file:

POST /api/v1/users/FUZZ HTTP/1.1
Host: target.com
User-Agent: Mozilla/5.0
Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...
Cookie: session=abc123xyz; csrftoken=def456
Content-Type: application/json
Content-Length: 27

{"action":"view","id":"1"}

Use Cases:

• Fuzzing authenticated endpoints with complex auth headers
• Testing API endpoints with JWT tokens
• Fuzzing with CSRF tokens, session cookies, and custom headers
• Testing endpoints that require specific User-Agents or Accept headers
• POST/PUT/DELETE requests with authentication

Pro Tips:

• You can place FUZZ in multiple locations: URL path, headers, body
• Use -request-proto https if needed (default is https)
• Always use -ac to filter out authenticated "not found" or error responses
• Great for IDOR testing: fuzz user IDs, document IDs, etc. in authenticated contexts

# Common authenticated fuzzing patterns
ffuf --request req.txt -w user_ids.txt -ac -mc 200 -o results.json

# With multiple FUZZ positions using custom keywords
ffuf --request req.txt -w endpoints.txt:ENDPOINT -w ids.txt:ID -mode pitchfork -ac

Proxy Usage

# HTTP proxy (useful for Burp Suite)
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -x http://127.0.0.1:8080

# SOCKS5 proxy
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -x socks5://127.0.0.1:1080

# Replay matched requests through proxy
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -replay-proxy http://127.0.0.1:8080

Cookie and Authentication

# Using cookies
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -b "sessionid=abc123; token=xyz789"

# Client certificate authentication
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -cc client.crt -ck client.key

Encoding

# URL encoding
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -enc 'FUZZ:urlencode'

# Multiple encodings
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -enc 'FUZZ:urlencode b64encode'

Testing for Vulnerabilities

# SQL injection testing
ffuf -w sqli_payloads.txt -u https://target.com/page.php?id=FUZZ -fs 1234

# XSS testing
ffuf -w xss_payloads.txt -u https://target.com/search?q=FUZZ -mr "<script>"

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

Batch Processing Multiple Targets

# 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

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

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.