Pandas for Pentesters
We are now living in a Big Data world – billions of devices communicating over millions of networks and generating
petabytes of data, both at rest and in transit! Security professionals now encounter Big Data in the form of large log files,
network traffic captures, forensics of large images and exports from security tools and products.
In this course, we will look at how to analyze, mangle, transform and visualize data to derive interesting insights
and intelligence from it.
Pandas is a Python library which is part of SciPy scientific computing ecosystem. In simple terms, Pandas provides
powerful data structures to perform data analysis. As dry as this might initially sound, due to the high level of abstraction
provided by its powerful API, Pandas allows us to do really complicated analysis with just a few lines of Python code.
In this course, we will go through the basics of Numpy, a deep dive into Pandas Series and Dataframes and
how to analyze data with it. The case study used is analysis of Wi-Fi networks using Airodump-NG’s output file
for a relatively large network with hundreds of devices.
A non-exhaustive list of topics covered include:
- Why Pandas for Pentesters?
- Lab Setup – Python, Anaconda, Jupyter
- Numpy basics
- Pandas Series
- Vector, Logical, String Operations
- Pandas Dataframes
- Filters, Operations, Apply
- Groupby, Split-Apply-Combine
- Aggregate, Transform, Filter
- Airodump-NG Scan Data
- Access Point Analysis
- Client Analysis
- Data Visualization
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