Metadata-Version: 1.1
Name: wad
Version: 0.4.1
Summary: A tool for detecting technologies used by web applications.
Home-page: https://github.com/CERN-CERT/WAD
Author: Sebastian Lopienski
Author-email: sebastian.lopienski@cern.ch
License: GPLv3
Description: WAD - Web application detector
        ==============================
        
        |Build Status| |PyPI|
        
        WAD lets you analyze given URL(s) and detect technologies used by web
        application behind that URL, from the OS and web server level, to the
        programming platform and frameworks, as well as server- and client-side
        applications, tools and libraries.
        
        For example, results of scan of server might include:
        
        -  OS: Windows, Linux...
        -  Web server: Apache, Nginx, IIS...
        -  Programming platform: PHP, Python, Ruby, Java...
        -  Content management systems: Drupal, WordPress...
        -  Frameworks: AngularJS, Ruby on Rails, Django...
        -  various databases, analytics tools, javascript libaries, CDNs,
           comment systems, search engines and many others.
        
        How it works
        ------------
        
        WAD is built as a standalone application, using
        `Wappalyzer <https://github.com/AliasIO/Wappalyzer>`__'s detection
        rules. It sends a GET request to the given URL and analyzes both HTTP
        response header and body (HTML page), looking for indications to
        discover web technologies used.
        
        Detection results may include information about versions of technologies
        used, for example Linux distro or Apache version. Results are
        categorized depending on type of technology (whether it is CMS or
        database etc.). There are now over 700 technologies that can be
        discovered using WAD.
        
        Installation
        ------------
        
        `WAD is available via PyPI <https://pypi.python.org/pypi/wad>`__, so in
        order to install it, you simply need to run following command:
        
        ``pip install wad``
        
        Usage
        -----
        
        Use ``wad -h`` to print help text. JSON is used by default for
        formatting output data, but you can also use other formats with -f
        option. ### Example usage scenario Command:
        ``wad -u https://pypi.python.org/``
        
        Output:
        
        ::
        
            {
                "https://pypi.python.org/pypi": [
                    {
                        "type": "cache-tools", 
                        "app": "Varnish", 
                        "ver": null
                    }, 
                    {
                        "type": "web-servers", 
                        "app": "Nginx", 
                        "ver": "1.6.2"
                    }
                ]
            }
        
        Differences between WAD and Wappalyzer
        --------------------------------------
        
        Although most of the rules matching functionality is simply a Python
        port of Wappalyzer's javascript implementation, there are some key
        differences between projects.
        
        First of all, Wappalyzer (as an extension) runs on top of web browser,
        which means that the scripts on scanned site were ran, so variables and
        objects are created and accessible. Unfortunately, this isn't and won't
        be a case for WAD. WAD parses raw site content (as delivered by HTTP
        response), without running it in browser context. The consequences of
        that are simple - we can't use Wappalyzer's rules, that search for
        variables and objects in Javascript environment.
        
        Secondly, the project has and will continue to naturally diverge from
        Wappalyzer's codebase. We don't aim to make one-to-one port of
        Wappalyzer project and with intention to move to BeautifulSoup as DOM
        inspector (instead of blindly parsing the website with regex), we won't
        be able to assure same behaviour in every case.
        
        Finally, additional features added into WAD project aren't ported into
        Wappalyzer at the same time.
        
        Changelog
        ---------
        
        0.4.1 (2020-02-26)
        ~~~~~~~~~~~~~~~~~~
        
        -  Restored project long description on pypi
        
        0.4 (2020-02-26)
        ~~~~~~~~~~~~~~~~
        
        -  Updated to latest apps.json, usability improvements
        
        0.3.4 (2015-08-25)
        ~~~~~~~~~~~~~~~~~~
        
        -  Added additional\_checks method, that allows further customization of
           Detector class
        
        0.3.3 (2015-08-17)
        ~~~~~~~~~~~~~~~~~~
        
        -  Fixed bug causing crash on SSL certificate mismatch in Python >=
           2.7.9
        
        0.3.2 (2015-08-17)
        ~~~~~~~~~~~~~~~~~~
        
        -  Fixed bug causing detection of Perl if the website had Polish (.pl)
           top-level domain
        -  Tests refactoring (duplicate code into method)
        
        0.3.1 (2015-08-17)
        ~~~~~~~~~~~~~~~~~~
        
        -  Package should be thread-safe now
        -  Minor changes to HumanReadableOutput
        
        0.3.0 (2015-08-13)
        ~~~~~~~~~~~~~~~~~~
        
        -  Added results grouping functionality
        
        0.2.0 (2015-08-10)
        ~~~~~~~~~~~~~~~~~~
        
        -  Multiple output formats (added Human readable text, CSV)
        -  Some methods extracted from Detector's detect method.
        -  Minor bugfixes
        
        .. |Build Status| image:: https://travis-ci.org/CERN-CERT/WAD.svg?branch=master
           :target: https://travis-ci.org/CERN-CERT/WAD
        .. |PyPI| image:: https://img.shields.io/pypi/v/wad.svg
           :target: https://pypi.python.org/pypi/wad
        
        
        Authors
        ~~~~~~~
        
        (Hopefully complete) list of people who contributed to this project:
        
        -  Sebastian Łopieński
        -  Piotr Lizończyk
        -  Vincent Brillaut
        -  Farzaneh Moghaddam
        -  Antonio Perez Perez
        -  Dame Jovanoski
        
        Special thanks to Elbert Alias, the author of Wappalyzer.
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Security
Classifier: Topic :: Internet :: WWW/HTTP
Requires: six
