Unlike regression models, where the model predicts a continuous number, classification models are used to predict a category among a given list of categories. The business problem discussed previously, where we have data related to customers of an e-commerce website over the last three months containing the purchase history of a particular product as (c_id, p_id, age, gender, nationality, salary, purchased[yes/no]). Our objective, as before, is to identify a customer who would be likely to purchase the product based upon their purchase history. Based on the permutation of all independent variables (age, gender, nationality, salary), a classification model can make a prediction in terms of 1 and 0, 1 being the prediction that a given customer will purchase the product, and 0 being that they won't. In this particular case, there are two categories (0 and...
Hands-On Penetration Testing with Python
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Hands-On Penetration Testing with Python
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Overview of this book
With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers.
Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you’ll explore the advanced uses of Python in the domain of penetration testing and optimization. You’ll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you’ll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python.
By the end of this book, you’ll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits.
Table of Contents (18 chapters)
Preface
Free Chapter
Introduction to Python
Building Python Scripts
Concept Handling
Advanced Python Modules
Vulnerability Scanner Python - Part 1
Vulnerability Scanner Python - Part 2
Machine Learning and Cybersecurity
Automating Web Application Scanning - Part 1
Automated Web Application Scanning - Part 2
Building a Custom Crawler
Reverse Engineering Linux Applications
Reverse Engineering Windows Applications
Exploit Development
Cyber Threat Intelligence
Other Wonders of Python
Assessments
Other Books You May Enjoy
Customer Reviews