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)

Parsing WAL files – wal_crawler.py

Now that we understand how a WAL file is structured and what data type we'll use to store data, we can begin planning the script. As we're working with a large binary object, we'll make great use of the struct library. We first introduced struct in Chapter 6, Extracting Artifacts from Binary Files, and have used it whenever dealing with binary files. Therefore, we won't repeat the basics of struct in this chapter.

The goal of our wal_crawler.py script is to parse the content of the WAL file, extract and write the cell content to a CSV file, and, optionally, run regular expression modules against the extracted data. This script is considered more advanced due to the complexity of the underlying object we're parsing. However, all we're doing here is applying what we've learned in the previous chapters at...