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  • Language
    Python
  • License
    GNU General Publi...
  • Created over 9 years ago
  • Updated over 6 years ago

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Repository Details

massive SQL injection vulnerability scanner

SQLiv

Massive SQL injection scanner

Features

  1. multiple domain scanning with SQL injection dork by Bing, Google, or Yahoo
  2. targetted scanning by providing specific domain (with crawling)
  3. reverse domain scanning

both SQLi scanning and domain info checking are done in multiprocessing
so the script is super fast at scanning many urls

quick tutorial & screenshots are shown at the bottom
project contribution tips at the bottom


Installation

  1. git clone https://github.com/the-robot/sqliv.git
  2. sudo python2 setup.py -i

Dependencies

Pre-installed Systems


Quick Tutorial

1. Multiple domain scanning with SQLi dork

  • it simply search multiple websites from given dork and scan the results one by one
python sqliv.py -d <SQLI DORK> -e <SEARCH ENGINE>  
python sqliv.py -d "inurl:index.php?id=" -e google  

2. Targetted scanning

  • can provide only domain name or specifc url with query params
  • if only domain name is provided, it will crawl and get urls with query
  • then scan the urls one by one
python sqliv.py -t <URL>  
python sqliv.py -t www.example.com  
python sqliv.py -t www.example.com/index.php?id=1  

3. Reverse domain and scanning

  • do reverse domain and look for websites that hosted on same server as target url
python sqliv.py -t <URL> -r

4. Dumping scanned result

  • you can dump the scanned results as json by giving this argument
python sqliv.py -d <SQLI DORK> -e <SEARCH ENGINE> -o result.json

View help

python sqliv.py --help

usage: sqliv.py [-h] [-d D] [-e E] [-p P] [-t T] [-r]

optional arguments:
  -h, --help  show this help message and exit
  -d D        SQL injection dork
  -e E        search engine [Google only for now]
  -p P        number of websites to look for in search engine
  -t T        scan target website
  -r          reverse domain

screenshots

1 2 3 4


Development

TODO

  1. POST form SQLi vulnerability testing

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