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Python: Penetration Testing for Developers

You're reading from   Python: Penetration Testing for Developers Execute effective tests to identify software vulnerabilities

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Product type Course
Published in Oct 2016
Publisher Packt
ISBN-13 9781787128187
Length 650 pages
Edition 1st Edition
Languages
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Authors (6):
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Christopher Duffy Christopher Duffy
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Christopher Duffy
Mohit Raj Mohit Raj
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Mohit Raj
Dave Mound Dave Mound
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Dave Mound
Terry Ip Terry Ip
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Terry Ip
Cameron Buchanan Cameron Buchanan
Author Profile Icon Cameron Buchanan
Cameron Buchanan
Andrew Mabbitt Andrew Mabbitt
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Andrew Mabbitt
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Table of Contents (32) Chapters Close

Python: Penetration Testing for Developers
Python: Penetration Testing for Developers
Credits
Preface
1. Understanding the Penetration Testing Methodology FREE CHAPTER 2. The Basics of Python Scripting 3. Identifying Targets with Nmap, Scapy, and Python 4. Executing Credential Attacks with Python 5. Exploiting Services with Python 6. Assessing Web Applications with Python 7. Cracking the Perimeter with Python 8. Exploit Development with Python, Metasploit, and Immunity 9. Automating Reports and Tasks with Python 10. Adding Permanency to Python Tools 11. Python with Penetration Testing and Networking 12. Scanning Pentesting 13. Sniffing and Penetration Testing 14. Wireless Pentesting 15. Foot Printing of a Web Server and a Web Application 16. Client-side and DDoS Attacks 17. Pentesting of SQLI and XSS 18. Gathering Open Source Intelligence 19. Enumeration 20. Vulnerability Identification 21. SQL Injection 22. Web Header Manipulation 23. Image Analysis and Manipulation 24. Encryption and Encoding 25. Payloads and Shells 26. Reporting Bibliography
Index

Finding e-mail addresses from web pages


Instead of generating your own e-mail list, you may find that a target organisation will have some that exist on their web pages. This may prove to be of higher value than e-mail addresses you have generated yourself as the likelihood of e-mail addresses on a target organisation's website being valid will be much higher than ones you have tried to guess.

Getting ready

For this recipe, you will need a list of pages you want to parse for e-mail addresses. You may want to visit the target organization's website and search for a sitemap. A sitemap can then be parsed for links to pages that exist within the website.

How to do it…

The following code will parse through responses from a list of URLs for instances of text that match an e-mail address format and save them to a file:

import urllib2
import re
import time
from random import randint
regex = re.compile(("([a-z0-9!#$%&'*+\/=?^_'{|}~-]+(?:\.[a-z0- 9!#$%&'*+\/=?^_'"
                    "{|}~-]+)...
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