Book Image

Hands-On Penetration Testing with Python

By : Furqan Khan
Book Image

Hands-On Penetration Testing with Python

By: Furqan Khan

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)

Parsing Twitter tweets

Being in the offensive security domain, we might wonder why we need to parse Twitter tweets. This question is valid, as this use case is more suited to defensive security. It may help, however, to uncover a good amount of information if we are targeting a specific individual or a specific organization.

As mentioned earlier, Twitter-tweet-parsing can be used by cyber intelligence teams to see if any defamation or sensitive content has been posted under the organization's name. Let's take a look at the following example that explains Twitter tweet parsing. First, we need to install the Python module as follows:

pip3 install tweet_parser

Our example takes a Twitter feed as an input JSON file and parses all tweets to produce the output. Let's create a file called sample.py as shown:

Let's use a sample Twitter feed file called exp.json as...