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Mastering Python for Networking and Security

You're reading from   Mastering Python for Networking and Security Leverage the scripts and libraries of Python version 3.7 and beyond to overcome networking and security issues

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781839217166
Length 538 pages
Edition 2nd Edition
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Author (1):
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José Manuel Ortega José Manuel Ortega
Author Profile Icon José Manuel Ortega
José Manuel Ortega
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Toc

Table of Contents (22) Chapters Close

Preface 1. Section 1: The Python Environment and System Programming Tools
2. Chapter 1: Working with Python Scripting FREE CHAPTER 3. Chapter 2: System Programming Packages 4. Section 2: Network Scripting and Extracting Information from the Tor Network with Python
5. Chapter 3: Socket Programming 6. Chapter 4: HTTP Programming 7. Chapter 5: Connecting to the Tor Network and Discovering Hidden Services 8. Section 3: Server Scripting and Port Scanning with Python
9. Chapter 6: Gathering Information from Servers 10. Chapter 7: Interacting with FTP, SFTP, and SSH Servers 11. Chapter 8: Working with Nmap Scanner 12. Section 4: Server Vulnerabilities and Security in Python Modules
13. Chapter 9: Interacting with Vulnerability Scanners 14. Chapter 10: Identifying Server Vulnerabilities in Web Applications 15. Chapter 11: Security and Vulnerabilities in Python Modules 16. Section 5: Python Forensics
17. Chapter 12: Python Tools for Forensics Analysis 18. Chapter 13: Extracting Geolocation and Metadata from Documents, Images, and Browsers 19. Chapter 14: Cryptography and Steganography 20. Assessments 21. Other Books You May Enjoy

Chapter 2 – System Programming Packages

  1. The system (sys) module.
  2. subprocess.call(“cls”, shell=True)
  3. We can use the context manager approach and the with statement.
  4. Processes are full programs. Threads are similar to processes: they are also code in execution. The difference is that threads are executed within a process and the threads of a process share resources among themselves, such as memory.
  5. The execution of threads in Python is controlled by the Global Interpreter Lock (GIL) so that only one thread can be executed at any time, independently of the number of processors with which the machine counts.
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