dast-ffuf
Fast web fuzzer for DAST testing with directory enumeration, parameter fuzzing, and virtual host discovery. Written in Go for high-performance HTTP fuzzing with extensive filtering capabilities. Supports multiple fuzzing modes (clusterbomb, pitchfork, sniper) and recursive scanning. Use when: (1) Discovering hidden directories, files, and endpoints on web applications, (2) Fuzzing GET and POST parameters to identify injection vulnerabilities, (3) Enumerating virtual hosts and subdomains, (4) Testing authentication endpoints with credential fuzzing, (5) Finding backup files and sensitive data exposures, (6) Performing comprehensive web application reconnaissance.
Best use case
dast-ffuf is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Fast web fuzzer for DAST testing with directory enumeration, parameter fuzzing, and virtual host discovery. Written in Go for high-performance HTTP fuzzing with extensive filtering capabilities. Supports multiple fuzzing modes (clusterbomb, pitchfork, sniper) and recursive scanning. Use when: (1) Discovering hidden directories, files, and endpoints on web applications, (2) Fuzzing GET and POST parameters to identify injection vulnerabilities, (3) Enumerating virtual hosts and subdomains, (4) Testing authentication endpoints with credential fuzzing, (5) Finding backup files and sensitive data exposures, (6) Performing comprehensive web application reconnaissance.
Fast web fuzzer for DAST testing with directory enumeration, parameter fuzzing, and virtual host discovery. Written in Go for high-performance HTTP fuzzing with extensive filtering capabilities. Supports multiple fuzzing modes (clusterbomb, pitchfork, sniper) and recursive scanning. Use when: (1) Discovering hidden directories, files, and endpoints on web applications, (2) Fuzzing GET and POST parameters to identify injection vulnerabilities, (3) Enumerating virtual hosts and subdomains, (4) Testing authentication endpoints with credential fuzzing, (5) Finding backup files and sensitive data exposures, (6) Performing comprehensive web application reconnaissance.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "dast-ffuf" skill to help with this workflow task. Context: Fast web fuzzer for DAST testing with directory enumeration, parameter fuzzing, and virtual host discovery. Written in Go for high-performance HTTP fuzzing with extensive filtering capabilities. Supports multiple fuzzing modes (clusterbomb, pitchfork, sniper) and recursive scanning. Use when: (1) Discovering hidden directories, files, and endpoints on web applications, (2) Fuzzing GET and POST parameters to identify injection vulnerabilities, (3) Enumerating virtual hosts and subdomains, (4) Testing authentication endpoints with credential fuzzing, (5) Finding backup files and sensitive data exposures, (6) Performing comprehensive web application reconnaissance.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/dast-ffuf/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How dast-ffuf Compares
| Feature / Agent | dast-ffuf | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Fast web fuzzer for DAST testing with directory enumeration, parameter fuzzing, and virtual host discovery. Written in Go for high-performance HTTP fuzzing with extensive filtering capabilities. Supports multiple fuzzing modes (clusterbomb, pitchfork, sniper) and recursive scanning. Use when: (1) Discovering hidden directories, files, and endpoints on web applications, (2) Fuzzing GET and POST parameters to identify injection vulnerabilities, (3) Enumerating virtual hosts and subdomains, (4) Testing authentication endpoints with credential fuzzing, (5) Finding backup files and sensitive data exposures, (6) Performing comprehensive web application reconnaissance.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# ffuf - Fast Web Fuzzer
## Overview
ffuf is a fast web fuzzer written in Go designed for discovering hidden resources, testing parameters, and performing comprehensive web application reconnaissance. It uses the FUZZ keyword as a placeholder for wordlist entries and supports advanced filtering, multiple fuzzing modes, and recursive scanning for thorough security assessments.
## Installation
```bash
# Using Go
go install github.com/ffuf/ffuf/v2@latest
# Using package managers
# Debian/Ubuntu
apt install ffuf
# macOS
brew install ffuf
# Or download pre-compiled binary from GitHub releases
```
## Quick Start
Basic directory fuzzing:
```bash
# Directory discovery
ffuf -u https://example.com/FUZZ -w /usr/share/wordlists/dirb/common.txt
# File discovery with extension
ffuf -u https://example.com/FUZZ -w wordlist.txt -e .php,.html,.txt
# Virtual host discovery
ffuf -u https://example.com -H "Host: FUZZ.example.com" -w subdomains.txt
```
## Core Workflows
### Workflow 1: Directory and File Enumeration
For discovering hidden resources on web applications:
1. Start with common directory wordlist:
```bash
ffuf -u https://target.com/FUZZ \
-w /usr/share/seclists/Discovery/Web-Content/common.txt \
-mc 200,204,301,302,307,401,403 \
-o results.json
```
2. Review discovered directories (focus on 200, 403 status codes)
3. Enumerate files in discovered directories:
```bash
ffuf -u https://target.com/admin/FUZZ \
-w /usr/share/seclists/Discovery/Web-Content/raft-small-files.txt \
-e .php,.bak,.txt,.zip \
-mc all -fc 404
```
4. Use recursive mode for deep enumeration:
```bash
ffuf -u https://target.com/FUZZ \
-w wordlist.txt \
-recursion -recursion-depth 2 \
-e .php,.html \
-v
```
5. Document findings and test discovered endpoints
### Workflow 2: Parameter Fuzzing (GET/POST)
Progress:
[ ] 1. Identify target endpoint for parameter testing
[ ] 2. Fuzz GET parameter names to discover hidden parameters
[ ] 3. Fuzz parameter values for injection vulnerabilities
[ ] 4. Test POST parameters with JSON/form data
[ ] 5. Apply appropriate filters to reduce false positives
[ ] 6. Analyze responses for anomalies and vulnerabilities
[ ] 7. Validate findings manually
[ ] 8. Document vulnerable parameters and payloads
Work through each step systematically. Check off completed items.
**GET Parameter Name Fuzzing:**
```bash
ffuf -u https://target.com/api?FUZZ=test \
-w /usr/share/seclists/Discovery/Web-Content/burp-parameter-names.txt \
-fs 0 # Filter out empty responses
```
**GET Parameter Value Fuzzing:**
```bash
ffuf -u https://target.com/api?id=FUZZ \
-w payloads.txt \
-mc all
```
**POST Data Fuzzing:**
```bash
# Form data
ffuf -u https://target.com/login \
-X POST \
-d "username=admin&password=FUZZ" \
-w passwords.txt \
-H "Content-Type: application/x-www-form-urlencoded"
# JSON data
ffuf -u https://target.com/api/login \
-X POST \
-d '{"username":"admin","password":"FUZZ"}' \
-w passwords.txt \
-H "Content-Type: application/json"
```
### Workflow 3: Virtual Host and Subdomain Discovery
For identifying virtual hosts and subdomains:
1. Prepare subdomain wordlist (or use SecLists)
2. Run vhost fuzzing:
```bash
ffuf -u https://target.com \
-H "Host: FUZZ.target.com" \
-w /usr/share/seclists/Discovery/DNS/subdomains-top1million-5000.txt \
-fs 0 # Filter by response size to identify valid vhosts
```
3. Filter results by comparing response sizes/words
4. Verify discovered vhosts manually
5. Enumerate directories on each vhost
6. Document vhost configurations and exposed services
### Workflow 4: Authentication Endpoint Fuzzing
For testing login forms and authentication mechanisms:
1. Identify authentication endpoint
2. Fuzz usernames:
```bash
ffuf -u https://target.com/login \
-X POST \
-d "username=FUZZ&password=test123" \
-w usernames.txt \
-H "Content-Type: application/x-www-form-urlencoded" \
-mr "Invalid password|Incorrect password" # Match responses indicating valid user
```
3. For identified users, fuzz passwords:
```bash
ffuf -u https://target.com/login \
-X POST \
-d "username=admin&password=FUZZ" \
-w /usr/share/seclists/Passwords/Common-Credentials/10-million-password-list-top-1000.txt \
-H "Content-Type: application/x-www-form-urlencoded" \
-fc 401,403 # Filter failed attempts
```
4. Use clusterbomb mode for combined username/password fuzzing:
```bash
ffuf -u https://target.com/login \
-X POST \
-d "username=FUZZ1&password=FUZZ2" \
-w usernames.txt:FUZZ1 \
-w passwords.txt:FUZZ2 \
-mode clusterbomb
```
### Workflow 5: Backup and Sensitive File Discovery
For finding exposed backup files and sensitive data:
1. Create wordlist of common backup patterns
2. Fuzz for backup files:
```bash
ffuf -u https://target.com/FUZZ \
-w backup-files.txt \
-e .bak,.backup,.old,.zip,.tar.gz,.sql,.7z \
-mc 200 \
-o backup-files.json
```
3. Test common sensitive file locations:
```bash
ffuf -u https://target.com/FUZZ \
-w /usr/share/seclists/Discovery/Web-Content/sensitive-files.txt \
-mc 200,403
```
4. Download and analyze discovered files
5. Report findings with severity classification
## Fuzzing Modes
ffuf supports multiple fuzzing modes for different attack scenarios:
**Clusterbomb Mode** - Cartesian product of all wordlists (default):
```bash
ffuf -u https://target.com/FUZZ1/FUZZ2 \
-w dirs.txt:FUZZ1 \
-w files.txt:FUZZ2 \
-mode clusterbomb
```
Tests every combination: dir1/file1, dir1/file2, dir2/file1, dir2/file2
**Pitchfork Mode** - Parallel iteration of wordlists:
```bash
ffuf -u https://target.com/login \
-X POST \
-d "username=FUZZ1&password=FUZZ2" \
-w users.txt:FUZZ1 \
-w passwords.txt:FUZZ2 \
-mode pitchfork
```
Tests pairs: user1/pass1, user2/pass2 (stops at shortest wordlist)
**Sniper Mode** - One wordlist, multiple positions:
```bash
ffuf -u https://target.com/FUZZ \
-w wordlist.txt \
-mode sniper
```
Standard single-wordlist fuzzing.
## Filtering and Matching
Effective filtering is crucial for reducing noise:
**Match Filters** (only show matching):
- `-mc 200,301` - Match HTTP status codes
- `-ms 1234` - Match response size
- `-mw 100` - Match word count
- `-ml 50` - Match line count
- `-mr "success|admin"` - Match regex pattern in response
**Filter Options** (exclude matching):
- `-fc 404,403` - Filter status codes
- `-fs 0,1234` - Filter response sizes
- `-fw 0` - Filter word count
- `-fl 0` - Filter line count
- `-fr "error|not found"` - Filter regex pattern
**Auto-Calibration:**
```bash
# Automatically filter baseline responses
ffuf -u https://target.com/FUZZ -w wordlist.txt -ac
```
## Common Patterns
### Pattern 1: API Endpoint Discovery
Discover REST API endpoints:
```bash
# Enumerate API paths
ffuf -u https://api.target.com/v1/FUZZ \
-w /usr/share/seclists/Discovery/Web-Content/api/api-endpoints.txt \
-mc 200,201,401,403 \
-o api-endpoints.json
# Fuzz API versions
ffuf -u https://api.target.com/FUZZ/users \
-w <(seq 1 10 | sed 's/^/v/') \
-mc 200
```
### Pattern 2: Extension Fuzzing
Test multiple file extensions:
```bash
# Brute-force extensions on known files
ffuf -u https://target.com/admin.FUZZ \
-w /usr/share/seclists/Discovery/Web-Content/web-extensions.txt \
-mc 200
# Or use -e flag for multiple extensions
ffuf -u https://target.com/FUZZ \
-w filenames.txt \
-e .php,.asp,.aspx,.jsp,.html,.bak,.txt
```
### Pattern 3: Rate-Limited Fuzzing
Respect rate limits and avoid detection:
```bash
# Add delay between requests
ffuf -u https://target.com/FUZZ \
-w wordlist.txt \
-p 0.5-1.0 # Random delay 0.5-1.0 seconds
# Limit concurrent requests
ffuf -u https://target.com/FUZZ \
-w wordlist.txt \
-t 5 # Only 5 concurrent threads
```
### Pattern 4: Custom Header Fuzzing
Fuzz HTTP headers for security misconfigurations:
```bash
# Fuzz custom headers
ffuf -u https://target.com/admin \
-w headers.txt:HEADER \
-H "HEADER: true" \
-mc all
# Fuzz header values
ffuf -u https://target.com/admin \
-H "X-Forwarded-For: FUZZ" \
-w /usr/share/seclists/Fuzzing/IPs.txt \
-mc 200
```
### Pattern 5: Cookie Fuzzing
Test cookie-based authentication and session management:
```bash
# Fuzz cookie values
ffuf -u https://target.com/dashboard \
-b "session=FUZZ" \
-w session-tokens.txt \
-mc 200
# Fuzz cookie names
ffuf -u https://target.com/admin \
-b "FUZZ=admin" \
-w cookie-names.txt
```
## Output Formats
Save results in multiple formats:
```bash
# JSON output (recommended for parsing)
ffuf -u https://target.com/FUZZ -w wordlist.txt -o results.json -of json
# CSV output
ffuf -u https://target.com/FUZZ -w wordlist.txt -o results.csv -of csv
# HTML report
ffuf -u https://target.com/FUZZ -w wordlist.txt -o results.html -of html
# All formats
ffuf -u https://target.com/FUZZ -w wordlist.txt -o results -of all
```
## Security Considerations
- **Sensitive Data Handling**: Discovered files may contain credentials, API keys, or PII. Handle findings securely and report responsibly
- **Access Control**: Only fuzz applications with proper authorization. Obtain written permission before testing third-party systems
- **Audit Logging**: Log all fuzzing activities including targets, wordlists used, and findings for compliance and audit trails
- **Compliance**: Ensure fuzzing activities comply with bug bounty program rules, penetration testing agreements, and legal requirements
- **Safe Defaults**: Use reasonable rate limits to avoid DoS conditions. Start with small wordlists before scaling up
## Integration Points
### Reconnaissance Workflow
1. Subdomain enumeration (amass, subfinder)
2. Port scanning (nmap)
3. Service identification
4. **ffuf directory/file enumeration**
5. Content discovery and analysis
6. Vulnerability scanning
### CI/CD Security Testing
Integrate ffuf into automated security pipelines:
```bash
# CI/CD script
#!/bin/bash
set -e
# Run directory enumeration
ffuf -u https://staging.example.com/FUZZ \
-w /wordlists/common.txt \
-mc 200,403 \
-o ffuf-results.json \
-of json
# Parse results and fail if sensitive files found
if grep -q "/.git/\|/backup/" ffuf-results.json; then
echo "ERROR: Sensitive files exposed!"
exit 1
fi
```
### Integration with Burp Suite
1. Use Burp to identify target endpoints
2. Export interesting requests
3. Convert to ffuf commands for automated fuzzing
4. Import ffuf results back to Burp for manual testing
## Troubleshooting
### Issue: Too Many False Positives
**Solution**: Use auto-calibration or manual filtering:
```bash
# Auto-calibration
ffuf -u https://target.com/FUZZ -w wordlist.txt -ac
# Manual filtering by size
ffuf -u https://target.com/FUZZ -w wordlist.txt -fs 1234,5678
```
### Issue: Rate Limiting or Blocking
**Solution**: Reduce concurrency and add delays:
```bash
ffuf -u https://target.com/FUZZ \
-w wordlist.txt \
-t 1 \
-p 2.0 \
-H "User-Agent: Mozilla/5.0..."
```
### Issue: Large Wordlist Takes Too Long
**Solution**: Start with smaller, targeted wordlists:
```bash
# Use top 1000 instead of full list
head -1000 /usr/share/seclists/Discovery/Web-Content/directory-list-2.3-medium.txt > small.txt
ffuf -u https://target.com/FUZZ -w small.txt
```
### Issue: Missing Discovered Content
**Solution**: Test with multiple extensions and match codes:
```bash
ffuf -u https://target.com/FUZZ \
-w wordlist.txt \
-e .php,.html,.txt,.asp,.aspx,.jsp \
-mc all \
-fc 404
```
## OWASP Testing Integration
Map ffuf usage to OWASP Testing Guide categories:
- **WSTG-CONF-04**: Review Old Backup and Unreferenced Files
- **WSTG-CONF-05**: Enumerate Infrastructure and Application Admin Interfaces
- **WSTG-CONF-06**: Test HTTP Methods
- **WSTG-IDENT-01**: Test Role Definitions (directory enumeration)
- **WSTG-ATHZ-01**: Test Directory Traversal/File Include
- **WSTG-INPVAL-01**: Test for Reflected Cross-site Scripting
- **WSTG-INPVAL-02**: Test for Stored Cross-site Scripting
## References
- [ffuf GitHub Repository](https://github.com/ffuf/ffuf)
- [SecLists Wordlists](https://github.com/danielmiessler/SecLists)
- [OWASP Web Security Testing Guide](https://owasp.org/www-project-web-security-testing-guide/)Related Skills
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