Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/JarryShaw/darc

Darkweb Crawler Project
https://github.com/JarryShaw/darc

crawler darkweb

Last synced: 12 days ago
JSON representation

Darkweb Crawler Project

Awesome Lists containing this project

README 

        
``darc`` - Darkweb Crawler Project

==================================



   For any technical and/or maintenance information,

   please kindly refer to the |docs|_.



.. |docs| replace:: **Official Documentation**

.. _docs: https://darc.jarryshaw.me



**NB**: Starting from version ``1.0.0``, new features of the project will not be

developed into this public repository. Only bugfix and security patches will be

applied to the update and new releases.



``darc`` is designed as a swiss army knife for darkweb crawling.

It integrates ``requests`` to collect HTTP request and response

information, such as cookies, header fields, etc. It also bundles

``selenium`` to provide a fully rendered web page and screenshot

of such view.



.. image:: https://darc.jarryshaw.me/en/latest/_images/darc.jpeg



The general process of ``darc`` can be described as following:



There are two types of *workers*:



* ``crawler`` -- runs the ``darc.crawl.crawler`` to provide a

  fresh view of a link and test its connectability



* ``loader`` -- run the ``darc.crawl.loader`` to provide an

  in-depth view of a link and provide more visual information



The general process can be described as following for *workers* of ``crawler`` type:



1. ``darc.process.process_crawler``: obtain URLs from the ``requests``

   link database (c.f. ``darc.db.load_requests``), and feed such URLs to

   ``darc.crawl.crawler``.



   **NOTE:**



      If ``darc.const.FLAG_MP`` is ``True``, the function will be

      called with *multiprocessing* support; if ``darc.const.FLAG_TH``

      if ``True``, the function will be called with *multithreading*

      support; if none, the function will be called in single-threading.



2. ``darc.crawl.crawler``: parse the URL using

   ``darc.link.parse_link``, and check if need to crawl the

   URL (c.f. ``darc.const.PROXY_WHITE_LIST``, ``darc.const.PROXY_BLACK_LIST``,

   ``darc.const.LINK_WHITE_LIST`` and ``darc.const.LINK_BLACK_LIST``);

   if true, then crawl the URL with ``requests``.



   If the URL is from a brand new host, ``darc`` will first try

   to fetch and save ``robots.txt`` and sitemaps of the host

   (c.f. ``darc.proxy.null.save_robots`` and ``darc.proxy.null.save_sitemap``),

   and extract then save the links from sitemaps (c.f. ``darc.proxy.null.read_sitemap``)

   into link database for future crawling (c.f. ``darc.db.save_requests``).

   Also, if the submission API is provided, ``darc.submit.submit_new_host``

   will be called and submit the documents just fetched.



   If ``robots.txt`` presented, and ``darc.const.FORCE`` is

   ``False``, ``darc`` will check if allowed to crawl the URL.



   **NOTE:**



      The root path (e.g. ``/`` in https://www.example.com/) will always

      be crawled ignoring ``robots.txt``.



   At this point, ``darc`` will call the customised hook function

   from ``darc.sites`` to crawl and get the final response object.

   ``darc`` will save the session cookies and header information,

   using ``darc.save.save_headers``.



   **NOTE:**



      If `requests.exceptions.InvalidSchema` is raised, the link

      will be saved by ``darc.proxy.null.save_invalid``. Further

      processing is dropped.



   If the content type of response document is not ignored (c.f.

   ``darc.const.MIME_WHITE_LIST`` and ``darc.const.MIME_BLACK_LIST``),

   ``darc.submit.submit_requests`` will be called and submit the document

   just fetched.



   If the response document is HTML (``text/html`` and ``application/xhtml+xml``),

   ``darc.parse.extract_links`` will be called then to extract all possible

   links from the HTML document and save such links into the database

   (c.f. ``darc.db.save_requests``).



   And if the response status code is between ``400`` and ``600``,

   the URL will be saved back to the link database

   (c.f. ``darc.db.save_requests``). If **NOT**, the URL will

   be saved into ``selenium`` link database to proceed next steps

   (c.f. ``darc.db.save_selenium``).



The general process can be described as following for *workers* of ``loader`` type:



1. ``darc.process.process_loader``: in the meanwhile, ``darc`` will

   obtain URLs from the ``selenium`` link database (c.f. ``darc.db.load_selenium``),

   and feed such URLs to ``darc.crawl.loader``.



   **NOTE:**



      If ``darc.const.FLAG_MP`` is ``True``, the function will be

      called with *multiprocessing* support; if ``darc.const.FLAG_TH``

      if ``True``, the function will be called with *multithreading*

      support; if none, the function will be called in single-threading.



2. ``darc.crawl.loader``: parse the URL using

   ``darc.link.parse_link`` and start loading the URL using

   ``selenium`` with Google Chrome.



   At this point, ``darc`` will call the customised hook function

   from ``darc.sites`` to load and return the original

   ``selenium.webdriver.chrome.webdriver.WebDriver`` object.



   If successful, the rendered source HTML document will be saved, and a

   full-page screenshot will be taken and saved.



   If the submission API is provided, ``darc.submit.submit_selenium``

   will be called and submit the document just loaded.



   Later, ``darc.parse.extract_links`` will be called then to

   extract all possible links from the HTML document and save such

   links into the ``requests`` database (c.f. ``darc.db.save_requests``).



------------

Installation

------------



**NOTE:**



   ``darc`` supports Python all versions above and includes **3.6**.

   Currently, it only supports and is tested on Linux (*Ubuntu 18.04*)

   and macOS (*Catalina*).



   When installing in Python versions below **3.8**, ``darc`` will

   use |walrus|_ to compile itself for backport compatibility.



   .. |walrus| replace:: ``walrus``

   .. _walrus: https://github.com/pybpc/walrus



.. code-block:: shell



   pip install python-darc



Please make sure you have Google Chrome and corresponding version of Chrome

Driver installed on your system.



   Starting from version **0.3.0**, we introduced `Redis`_ for the task

   queue database backend.



   .. _Redis: https://redis.io



   Since version **0.6.0**, we introduced relationship database storage

   (e.g. `MySQL`_, `SQLite`_, `PostgreSQL`_, etc.) for the task queue database

   backend, besides the `Redis`_ database, since it can be too much memory-costly

   when the task queue becomes vary large.



   .. _MySQL: https://mysql.com/

   .. _SQLite: https://www.sqlite.org/

   .. _PostgreSQL: https://www.postgresql.org/



   Please make sure you have one of the backend database installed, configured,

   and running when using the ``darc`` project.



However, the ``darc`` project is shipped with Docker and Compose support.

Please see the project root for relevant files and more information.



Or, you may refer to and/or install from the `Docker Hub`_ repository:



.. code-block:: shell



   docker pull jsnbzh/darc[:TAGNAME]



.. _Docker Hub: https://hub.docker.com/r/jsnbzh/darc



or GitHub Container Registry, with more updated and comprehensive images:



.. code-block:: shell



   docker pull ghcr.io/jarryshaw/darc[:TAGNAME]

   # or the debug image

   docker pull ghcr.io/jarryshaw/darc-debug[:TAGNAME]



-----

Usage

-----



The ``darc`` project provides a simple CLI::



   usage: darc [-h] [-v] -t {crawler,loader} [-f FILE] ...



   the darkweb crawling swiss army knife



   positional arguments:

     link                  links to craw



   optional arguments:

     -h, --help            show this help message and exit

     -v, --version         show program's version number and exit

     -t {crawler,loader}, --type {crawler,loader}

                           type of worker process

     -f FILE, --file FILE  read links from file



It can also be called through module entrypoint::



   python -m darc ...



**NOTE:**



   The link files can contain **comment** lines, which should start with ``#``.

   Empty lines and comment lines will be ignored when loading.