Table of Contents for
Python: Penetration Testing for Developers

Version ebook / Retour

Cover image for bash Cookbook, 2nd Edition Python: Penetration Testing for Developers by Dave Mound Published by Packt Publishing, 2016
  1. Cover
  2. Table of Contents
  3. Python: Penetration Testing for Developers
  4. Python: Penetration Testing for Developers
  5. Python: Penetration Testing for Developers
  6. Credits
  7. Preface
  8. What you need for this learning path
  9. Who this learning path is for
  10. Reader feedback
  11. Customer support
  12. 1. Module 1
  13. 1. Understanding the Penetration Testing Methodology
  14. Understanding what penetration testing is not
  15. Assessment methodologies
  16. The penetration testing execution standard
  17. Penetration testing tools
  18. Summary
  19. 2. The Basics of Python Scripting
  20. Python – the good and the bad
  21. A Python interactive interpreter versus a script
  22. Environmental variables and PATH
  23. Understanding dynamically typed languages
  24. The first Python script
  25. Developing scripts and identifying errors
  26. Python formatting
  27. Python variables
  28. Operators
  29. Compound statements
  30. Functions
  31. The Python style guide
  32. Arguments and options
  33. Your first assessor script
  34. Summary
  35. 3. Identifying Targets with Nmap, Scapy, and Python
  36. Understanding Nmap
  37. Nmap libraries for Python
  38. The Scapy library for Python
  39. Summary
  40. 4. Executing Credential Attacks with Python
  41. Identifying the target
  42. Creating targeted usernames
  43. Testing for users using SMTP VRFY
  44. Summary
  45. 5. Exploiting Services with Python
  46. Understanding the chaining of exploits
  47. Automating the exploit train with Python
  48. Summary
  49. 6. Assessing Web Applications with Python
  50. Identifying hidden files and directories with Python
  51. Credential attacks with Burp Suite
  52. Using twill to walk through the source
  53. Understanding when to use Python for web assessments
  54. Summary
  55. 7. Cracking the Perimeter with Python
  56. Understanding the link between accounts and services
  57. Cracking inboxes with Burp Suite
  58. Identifying the attack path
  59. Gaining access through websites
  60. Summary
  61. 8. Exploit Development with Python, Metasploit, and Immunity
  62. Understanding the Windows memory structure
  63. Understanding memory addresses and endianness
  64. Understanding the manipulation of the stack
  65. Understanding immunity
  66. Understanding basic buffer overflow
  67. Writing a basic buffer overflow exploit
  68. Understanding stack adjustments
  69. Understanding the purpose of local exploits
  70. Understanding other exploit scripts
  71. Reversing Metasploit modules
  72. Understanding protection mechanisms
  73. Summary
  74. 9. Automating Reports and Tasks with Python
  75. Understanding how to create a Python class
  76. Summary
  77. 10. Adding Permanency to Python Tools
  78. Understanding the difference between multithreading and multiprocessing
  79. Building industry-standard tools
  80. Summary
  81. 2. Module 2
  82. 1. Python with Penetration Testing and Networking
  83. Approaches to pentesting
  84. Introducing Python scripting
  85. Understanding the tests and tools you'll need
  86. Learning the common testing platforms with Python
  87. Network sockets
  88. Server socket methods
  89. Client socket methods
  90. General socket methods
  91. Moving on to the practical
  92. Summary
  93. 2. Scanning Pentesting
  94. What are the services running on the target machine?
  95. Summary
  96. 3. Sniffing and Penetration Testing
  97. Implementing a network sniffer using Python
  98. Learning about packet crafting
  99. Introducing ARP spoofing and implementing it using Python
  100. Testing the security system using custom packet crafting and injection
  101. Summary
  102. 4. Wireless Pentesting
  103. Wireless attacks
  104. Summary
  105. 5. Foot Printing of a Web Server and a Web Application
  106. Introducing information gathering
  107. Information gathering of a website from SmartWhois by the parser BeautifulSoup
  108. Banner grabbing of a website
  109. Hardening of a web server
  110. Summary
  111. 6. Client-side and DDoS Attacks
  112. Tampering with the client-side parameter with Python
  113. Effects of parameter tampering on business
  114. Introducing DoS and DDoS
  115. Summary
  116. 7. Pentesting of SQLI and XSS
  117. Types of SQL injections
  118. Understanding the SQL injection attack by a Python script
  119. Learning about Cross-Site scripting
  120. Summary
  121. 3. Module 3
  122. 1. Gathering Open Source Intelligence
  123. Gathering information using the Shodan API
  124. Scripting a Google+ API search
  125. Downloading profile pictures using the Google+ API
  126. Harvesting additional results from the Google+ API using pagination
  127. Getting screenshots of websites with QtWebKit
  128. Screenshots based on a port list
  129. Spidering websites
  130. 2. Enumeration
  131. Performing a ping sweep with Scapy
  132. Scanning with Scapy
  133. Checking username validity
  134. Brute forcing usernames
  135. Enumerating files
  136. Brute forcing passwords
  137. Generating e-mail addresses from names
  138. Finding e-mail addresses from web pages
  139. Finding comments in source code
  140. 3. Vulnerability Identification
  141. Automated URL-based Directory Traversal
  142. Automated URL-based Cross-site scripting
  143. Automated parameter-based Cross-site scripting
  144. Automated fuzzing
  145. jQuery checking
  146. Header-based Cross-site scripting
  147. Shellshock checking
  148. 4. SQL Injection
  149. Checking jitter
  150. Identifying URL-based SQLi
  151. Exploiting Boolean SQLi
  152. Exploiting Blind SQL Injection
  153. Encoding payloads
  154. 5. Web Header Manipulation
  155. Testing HTTP methods
  156. Fingerprinting servers through HTTP headers
  157. Testing for insecure headers
  158. Brute forcing login through the Authorization header
  159. Testing for clickjacking vulnerabilities
  160. Identifying alternative sites by spoofing user agents
  161. Testing for insecure cookie flags
  162. Session fixation through a cookie injection
  163. 6. Image Analysis and Manipulation
  164. Hiding a message using LSB steganography
  165. Extracting messages hidden in LSB
  166. Hiding text in images
  167. Extracting text from images
  168. Enabling command and control using steganography
  169. 7. Encryption and Encoding
  170. Generating an MD5 hash
  171. Generating an SHA 1/128/256 hash
  172. Implementing SHA and MD5 hashes together
  173. Implementing SHA in a real-world scenario
  174. Generating a Bcrypt hash
  175. Cracking an MD5 hash
  176. Encoding with Base64
  177. Encoding with ROT13
  178. Cracking a substitution cipher
  179. Cracking the Atbash cipher
  180. Attacking one-time pad reuse
  181. Predicting a linear congruential generator
  182. Identifying hashes
  183. 8. Payloads and Shells
  184. Extracting data through HTTP requests
  185. Creating an HTTP C2
  186. Creating an FTP C2
  187. Creating an Twitter C2
  188. Creating a simple Netcat shell
  189. 9. Reporting
  190. Converting Nmap XML to CSV
  191. Extracting links from a URL to Maltego
  192. Extracting e-mails to Maltego
  193. Parsing Sslscan into CSV
  194. Generating graphs using plot.ly
  195. A. Bibliography
  196. Index

Identifying hidden files and directories with Python

When we visit the site of the identified IP address, we see that it is the Damn Vulnerable Web Application (DVWA). We also see that it has appended the details of the default landing page to our initial request. This means that we start from the http://192.168.195.145/dvwa/login.php site as shown in the following screenshot:

Identifying hidden files and directories with Python

We now have a starting location to test from, and using these details, we can look for hidden directories and files. Let's modify our last script to automatically look for hidden files or directories.

The best way to do this is to start within the base directory of the site we are in. You can go up levels, but in environments where multiple websites are housed, you may end up jumping out of the scope. So, know your environment before proceeding to attack in that manner. As you can see, the script runs through a file of directories and filenames, which appends them to the target site. We are then reported whether they were valid or not:

#!/usr/bin/env python
import urllib2, argparse, sys
defhost_test(filename, host):
    file = "headrequests.log"
    bufsize = 0
    e = open(file, 'a', bufsize)
    print("[*] Reading file %s") % (file)
    with open(filename) as f:
        locations = f.readlines()
    for item in locations:
        target = host + "/" + item
        try:
            request = urllib2.Request(target)
            request.get_method = lambda : 'GET'
            response = urllib2.urlopen(request)
        except:
            print("[-] %s is invalid") % (str(target.rstrip('\n')))
            response = None
        if response != None:
            print("[+] %s is valid") % (str(target.rstrip('\n')))
            details = response.info()
            e.write(str(details))
    e.close()

Knowing this, we can load up four of the most common hidden or unlinked locations that websites house. These are admin, dashboard, robots.txt, and config. Using this data, when we run the script, we identify two viable locations, as shown in the following screenshot. Robots.txt is good, but config usually means we can find usernames and passwords if the permissions are incorrect or if the file is not in use by the web server.

Identifying hidden files and directories with Python

As you can see here, we get a listing of the directory's contents:

Identifying hidden files and directories with Python

Unfortunately, when you open the config.inc.php file, as shown in this screenshot, nothing is displayed:

Identifying hidden files and directories with Python

Administrators and support personnel do not always understand the impact of some of their actions. When backups are made from config files, if they are not actively being used, or if the permissions are not correctly set, you can often read them through a browser. A backup file on a Linux system is denoted by a trailing ~. We know that it is a Linux system because of the previous HEAD request, which showed that it was an Ubuntu host.

Tip

Remember that headers can be manipulated by administrators and security tools, so they should not be trusted as definitive sources of information.

As you can see in the following screenshot, the request opens up a config file that provides us the details required to access a database server, from which we can extract critical data:

Identifying hidden files and directories with Python

As a penetration tester, you have to be efficient with your time as mentioned previously it is one of the obstacles of a successful penetration test. This means that when we research the contents of a database, we can also set up some automated tools. A simple test would be to use Burp Suite using Intruder.

Note

The full version of the dirtester.py script can be found at https://raw.githubusercontent.com/funkandwagnalls/pythonpentest/master/dirtester.py.