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Onion Crawler

Scrape and Store Dark Web Sites along with therir Latency | Crawler for Dark Web | Search Engine Oriented


DOCS UI

Functionalities

  • It's implemented using BFS and in coming time it's implementation will be changed to A* Search (Preferential Crawler)

  • fetch onion links

  • recursive fetching

  • store scrapped data

  • user added url

  • url blacklisting


Increasing the crawler reach

Increase Crawl Depth
Add More starter links
Create more spiders with special focus on Directories

Spiders

  • DRL Link Dir Onion
    • A big directory of urls
  • UADD User Added
    • Added by user
    • presently links are appened in user_added_urls.txt under spider_data
    • Crawled in exactly similar fashion as to DRL

Instructions to run

Pre-requisites:

-  Py3
-  Tor

< directions to install >

pip install -r requirements.txt

< directions to execute > (For commit of Jul 10, 2020)

  • This commit contains pipeline to generate data in csv/json file
  • You can run this without much effort
# start tor on port 9150
pproxy -l http://:8181 -r socks5://127.0.0.1:9150 -vv
scrapy crawl name_of_spider # DRL

< directions to execute > (After commit Jul 10, 2020)

  • This commit contains data pipeline to save data on MongoDB Server
  • You need to setup MongoDB Server connection credentials and URI in settings.py/pipeline.py file

Sample JSON

Instructional Video

Bigger Datasets

StoryBoarding

Idea hamster: --

Developer: I had prior experience with web scraping but hadn't worked with web crawlers before and scraping the deep-web was also something new to me as it required setting up tor proxy. This project developed my interest in the web-mining subject and therefore it encorged me to take this subject as a subject in college curriculum.

Contributors

Idea by- Angad Sharma

1UC1F3R616 (Kush Choudhary)

1UC1F3R616

Github of Kush Choudhary aka 1UC1F3R616



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  • Python 89.8%
  • JavaScript 10.2%