XSStrike v3.1.2 released: advanced XSS detection and exploitation suite

XSStrike is an advanced XSS detection suite. It has a powerful fuzzing engine and provides zero false positive results using fuzzy matching. XSStrike is the first XSS scanner to generate its own payloads. It is intelligent enough to detect and break out of various contexts.

Why XSStrike?

Every XSS scanner out there has a list of payloads, they inject the payloads and if the payload is reflected into the webpage, it is declared vulnerable but that’s just stupid. XSStrike on the other hand analyses the response with multiple parsers and then crafts payloads that are guaranteed to work. Here are some examples of the payloads generated by XSStrike:

}]};(confirm)()//\
<A%0aONMouseOvER%0d=%0d[8].find(confirm)>z
</tiTlE/><a%0donpOintErentER%0d=%0d(prompt)``>z
</SCRiPT/><DETAILs/+/onpoINTERenTEr%0a=%0aa=prompt,a()//

 

Apart from that, XSStrike has crawled, fuzzing, WAF detection capabilities as well. It also scans for DOM XSS vulnerabilities.

Features

  • Reflected and DOM XSS Scanning
  • Multithreaded crawling
  • Context analysis
  • Configurable Core
  • Highly Researched Workflow
  • WAF detection & evasion
  • Handmade HTML & JavaScript parser
  • Powerful fuzzing engine
  • Intelligent payload generator
  • Complete HTTP Support
  • Powered by PhotonZetanize, and Arjun

Changelog

v3.1.2

  • Fixed POST data handling
  • Support for JSON POST data
  • Support for URL rewriting
  • Cleaner crawling dashboard
  • No more weird characters while scanning DOM
  • Better DOM XSS scanning
  • Handle Unicode while writing to file
  • Handle connection reset
  • Added the ability to add headers from the command line
  • Fixed issue which caused foundParams to not be tested

Installing

git clone https://github.com/s0md3v/XSStrike.git
cd XSStrike
pip install -r requirements.txt

Usage

python xsstrike

DOM XSS

 

Reflected XSS

 

Crawling

 

Hidden Parameter Discovery

 

Interactive HTTP Headers Prompt

 

Tutorial

Copyright (c) 2018 Somdev Sangwan

Source: https://github.com/s0md3v/

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