Book Image

Learning Python for Forensics - Second Edition

By : Preston Miller, Chapin Bryce
Book Image

Learning Python for Forensics - Second Edition

By: Preston Miller, Chapin Bryce

Overview of this book

Digital forensics plays an integral role in solving complex cybercrimes and helping organizations make sense of cybersecurity incidents. This second edition of Learning Python for Forensics illustrates how Python can be used to support these digital investigations and permits the examiner to automate the parsing of forensic artifacts to spend more time examining actionable data. The second edition of Learning Python for Forensics will illustrate how to develop Python scripts using an iterative design. Further, it demonstrates how to leverage the various built-in and community-sourced forensics scripts and libraries available for Python today. This book will help strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. By the end of this book, you will build a collection of Python scripts capable of investigating an array of forensic artifacts and master the skills of extracting metadata and parsing complex data structures into actionable reports. Most importantly, you will have developed a foundation upon which to build as you continue to learn Python and enhance your efficacy as an investigator.
Table of Contents (15 chapters)

Summary

This chapter focused on the use of databases in script development. We explored how to use and manipulate a SQLite database in Python to store and retrieve information about file listings. We discussed when and how a database is a correct solution to store this information, as it has a fixed data structure and could be a large dataset.

In addition, we discussed multiple methods of interacting with databases, a manual process to show how databases work at a lower level, and a more Pythonic example where a third-party module handles these low-level interactions for us. We also explored a new type of report, using HTML to create a different output that can be viewed without additional software, and manipulating it to add new styles and functionality as we see fit. Overall, this section builds on the underlying goal of demonstrating different ways we can use Python and supporting...