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Offensive Security Using Python

You're reading from   Offensive Security Using Python A hands-on guide to offensive tactics and threat mitigation using practical strategies

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781835468166
Length 248 pages
Edition 1st Edition
Languages
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Authors (2):
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Rejah Rehim Rejah Rehim
Author Profile Icon Rejah Rehim
Rejah Rehim
Manindar Mohan Manindar Mohan
Author Profile Icon Manindar Mohan
Manindar Mohan
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1:Python for Offensive Security
2. Chapter 1: Introducing Offensive Security and Python FREE CHAPTER 3. Chapter 2: Python for Security Professionals – Beyond the Basics 4. Part 2: Python in Offensive Web Security
5. Chapter 3: An Introduction to Web Security with Python 6. Chapter 4: Exploiting Web Vulnerabilities Using Python 7. Chapter 5: Cloud Espionage – Python for Cloud Offensive Security 8. Part 3: Python Automation for Advanced Security Tasks
9. Chapter 6: Building Automated Security Pipelines with Python Using Third-Party Tools 10. Chapter 7: Creating Custom Security Automation Tools with Python 11. Part 4: Python Defense Strategies for Robust Security
12. Chapter 8: Secure Coding Practices with Python 13. Chapter 9: Python-Based Threat Detection and Incident Response 14. Index 15. Other Books You May Enjoy

Advanced Python features

We can combine our library created in the earlier section into our network mapping tool and transform our code, which does a network scan and a port scan of the discovered IP addresses. Let us keep it there and talk about some more advanced Python features, starting with decorators.

Decorators

Decorators are a powerful aspect of Python’s syntax, allowing you to modify or enhance the behavior of functions or methods without changing their source code.

For an improved understanding of Python decorators, we will delve into the examination of the following code:

1. def timing_decorator(func):
2.     def wrapper(*args, **kwargs):
3.         start_time = time.time()  # Record the start time
4.         result = func(*args, **kwargs)  # Call the original function
5.        ...
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