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Tagged User Could Delete Facebook Story

I recently reached Bronze Hacker Plus League on the Facebook bug bounty program. So today, I will be sharing one of my recently resolved…Continue reading on Medium »
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How I Offered Free 1 Lakh Rupees Through Government Website?

Hey Hackers, It’s Me Krishnadev P Melevila, a 19-Year-old self-learned cyber security researcher.Continue reading on InfoSec Write-ups »
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Hacking Articles Tips Tricks Videos Tutorials

How I Offered Free 1 Lakh Rupees Through Government Website?

Hey Hackers, It’s Me Krishnadev P Melevila, a 19-Year-old self-learned cyber security researcher.
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SubCrawl - A Modular Framework For Discovering Open Directories, Identifying Unique Content Through Signatures And Organizing The Data With Optional Output Modules, Such As MISP
http://www.kitploit.com/2021/10/subcrawl-modular-framework-for.html

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Hacking Articles Tips Tricks Videos Tutorials

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Hacking Articles Tips Tricks Videos Tutorials

SubCrawl is a framework developed by Patrick Schläpfer (https://twitter.com/stoerchl), Josh Stroschein (https://twitter.com/jstrosch) and Alex Holland (https://twitter.com/cryptogramfan) of HP Inc’s Threat Research (https://threatresearch.ext.hp.com/blog/) team. SubCrawl is designed to find, scan and analyze open directories. The framework is modular, consisting of four components: input modules, processing modules, output modules and the core crawling engine. URLs are the primary input values, which the framework parses and adds to a queuing system before crawling them. The parsing of the URLs is an important first step, as this takes a submitted URL and generates additional URLs to be crawled by removing sub-directories, one at a time until none remain. This process ensures a more complete scan attempt of a web server and can lead to the discovery of additional content. Notably, SubCrawl does not use a brute-force (https://www.kitploit.com/search/label/Brute-force) method for discovering URLs. All the content scanned comes from the input URLs, the process of parsing the URL and discovery during crawling. When an open directory is discovered, the crawling engine extracts links from the directory for evaluation. The crawling engine determines if the link is another directory or if it is a file. Directories are added to the crawling queue, while files undergo additional analysis by the processing modules. Results are generated and stored for each scanned URL, such as the SHA256 and fuzzy hashes of the content, if an open directory was found, or matches against YARA rules. Finally, the result data is processed according to one or more output modules, of which there are currently three. The first provides integration with MISP, the second simply prints the data to the console, and the third stores the data in an SQLite database. Since the framework is modular, it is not only easy to configure which input, processing and output modules are desired, but also straightforward to develop new modules.

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stoerchl (@stoerchl) | Twitter

The latest Tweets from stoerchl (@stoerchl). Malware Analyst @HPSecurity | cycling enthusiast and blue jays fan!. Switzerland

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