See-SURF : Python Based Scanner To Find Potential SSRF Parameters

See-SURF is a Python based scanner to find potential SSRF parameters in a web application. SSRF being one of the critical vulnerabilities out there in web, i see there was no tool which would automate finding potential vulnerable parameters. See-SURF can be added to your arsenal for recon while doing bug hunting/web security testing.

Features

• Takes burp’s sitemap as input and parses and parses the file with a strong regex matches any GET/POST URL parameters containing potentially vulnerable SSRF keywords like URL/website etc. Also, checks the parameter values for any URL or IP address passed. Examples GET request –
  google.com/url=https://yahoo.com
  google.com/q=https://yahoo.com
  FORMS –
  <input name="url" placeholder="https://msn.com">
  
• Multi-threaded In-built crawler to run and gather as much data as possible to parse and identify potentially vulnerable SSRF parameters.
  
• Supply cookies for an authenticated scanning.
  
• By default, normal mode is On, with a verbose switch you would see the same vulnerable param in different endpoints. The same parameter may not be sanitized at all places. But verbose mode generates a lot of noise. Example:
  https://google.com/path/1/urlToConnect=https://yahoo.com
  https://google.com/differentpath/urlToConnect=https://yahoo.com
  
• Exploitation – Makes an external request to burp collaborator or any other http server with the vulnerable parameter to confirm the possibility of SSRF.
  

Also Read : CredNinja – A Multithreaded Tool Designed To Identify If Credentials Via SMB

How to use?

[-] This would run with default threads=10, no cookies/session and NO verbose mode

python3 see-surf.py -H https://www.google.com

[-] Space separate Cookies can be supplied for an authenticated session crawling

python3 see-surf.py -H https://www.google.com -c cookie_name1=value1 cookie_name2=value2

[-] Supplying no. of threads and verbose mode (Verbose Mode Is Not Recommended If You Don’t Want To Spend Longer Time But The Possibility Of Bug Finding Increases)

python3 see-surf.py -H https://www.google.com -c cookie_name1=value1 cookie_name2=value2 -t 20 -v

By Default, normal mode is On, with verbose switch you would see the same potential vulnerable param in different endpoints. (Same parameter may not be sanitized at all places. But verbose mode generates a lot of noise.)
Example:
https://google.com/abc/1/urlToConnect=https://yahoo.com
https://google.com/123/urlToConnect=https://yahoo.com

Version-2 (Best Recommended)

Burp Sitemap (-b switch) & Connect back automation ( -p switch )

Complete Command would look like this –

python3 see-surf.py -H https://www.google.com -c cookie_name1=value1 cookie_name2=value2 -b burp_file.xml -p http://72.72.72.72:8000

[-] -b switch Provide burp sitemap files for a better discovery of potential SSRF parameters. The script would first parse the burp file and try to identify potential params and then run the built in crawler on it

Browser the target with your burpsuite running at the background, make some GET/POST requests, the more the better. Then go to target, right click-> “Save selected Items” and save it. Provide to the script as follows.

python3 see-surf.py -H https://www.google.com -c cookie_name1=value1 cookie_name2=value2 -b burp_file.xml

)

[-] -p switch Fire up burpsuite collaborator and pass the host with -p parameter Or start a simple python http server and wait for the vulnerable param to execute your request. (Highly Recommended)
(This basically helps in exploiting GET requests, for POST you would need to try to exploit it manually)
Payload will get executed with the param at the end of the string so its easy to identify which one is vulnerable. For example: http://72.72.72.72:8000/vulnerableparam

python3 see-surf.py -H https://www.google.com -c cookie_name1=value1 cookie_name2=value2 -p http://72.72.72.72:8000

Installation

git clone https://github.com/In3tinct/See-SURF.git
cd See-SURF/
pip3 install BeautifulSoup4
pip3 install requests

Tests

A basic framework has been created. More tested would be added to reduce any false positives.