This project is a command line tool and python library that uses Wappalyzer extension (and its fingerprints) to detect technologies. Other projects emerged after discontinuation of the official open source project are using outdated fingerpints and lack accuracy when used on dynamic web-apps, this project bypasses those limitations.

• Installation
• For Users
• For Developers
• FAQ

Before installing wappalyzer, you will to install Firefox and geckodriver. Below are detailed steps for setting up geckodriver but you may use google/youtube for help.

pipx install wappalyzer

To use it as a library, install it with pip inside an isolated container e.g. venv or docker. You may also --break-system-packages to do a 'regular' install but it is not recommended.

git clone https://github.com/s0md3v/wappalyzer-next.git
cd wappalyzer-next

docker compose up -d

docker compose run --rm wappalyzer -i https://example.com

docker compose run --rm wappalyzer -i https://example.com -oJ output.json

Some common usage examples are given below, refer to list of all options for more information.

• Scan a single URL: wappalyzer -i https://example.com
• Scan multiple URLs from a file: wappalyzer -i urls.txt -t 10
• Scan with authentication: wappalyzer -i https://example.com -c "sessionid=abc123; token=xyz789"
• Export results to JSON: wappalyzer -i https://example.com -oJ results.json

Note: For accuracy use 'full' scan type (default). 'fast' and 'balanced' do not use browser emulation.

• -i: Input URL or file containing URLs (one per line)
• --scan-type: Scan type (default: 'full')
  • fast: Quick HTTP-based scan (sends 1 request)
  • balanced: HTTP-based scan with more requests
  • full: Complete scan using wappalyzer extension
• -t, --threads: Number of concurrent threads (default: 5)
• -oJ: JSON output file path
• -oC: CSV output file path
• -c, --cookie: Cookie header string for authenticated scans

The python library is a available on pypi as wappalyzer and can be imported with the same name.

The main function you'll interact with is analyze():

from wappalyzer import analyze

# Basic usage
results = analyze('https://example.com')

# With options
results = analyze(
    url='https://example.com',
    scan_type='full',  # 'fast', 'balanced', or 'full'
    threads=3,
    cookie='sessionid=abc123'
)

• url (str): The URL to analyze
• scan_type (str, optional): Type of scan to perform
  • 'fast': Quick HTTP-based scan
  • 'balanced': HTTP-based scan with more requests
  • 'full': Complete scan including JavaScript execution (default)
• threads (int, optional): Number of threads for parallel processing (default: 3)
• cookie (str, optional): Cookie header string for authenticated scans

Returns a dictionary with the URL as key and detected technologies as value:

{
  "https://github.com": {
    "Amazon S3": {"version": "", "confidence": 100, "categories": ["CDN"], "groups": ["Servers"]},
    "lit-html": {"version": "1.1.2", "confidence": 100, "categories": ["JavaScript libraries"], "groups": ["Web development"]},
    "React Router": {"version": "6", "confidence": 100, "categories": ["JavaScript frameworks"], "groups": ["Web development"]},
  "https://google.com" : {},
  "https://example.com" : {},
}}

Firefox extensions are .xpi files which are essentially zip files. This makes it easier to extract data and slightly modify the extension to make this tool work.

• fast: Sends a single HTTP request to the URL. Doesn't use the extension.
• balanced: Sends additional HTTP requests to .js files, /robots.txt annd does DNS queries. Doesn't use the extension.
• full: Uses the official Wappalyzer extension to scan the URL in a headless browser.