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)

Creating fuzzy hashes

Now that we've mastered how to generate cryptographic hashes, let's work on generating fuzzy hashes. We'll discuss a few techniques we could employ for similarity analysis, and walk through a basic example of how ssdeep and spamsum employ rolling hashing to help generate more resilient signatures.

It may go without saying that our most accurate approach to similarity analysis is to compare the byte content of two files, side by side, and look for differences. While we may be able to accomplish this using command-line tools or a difference analysis tool (such as kdiff3), this only really works at a small scale. Once we move from comparing two small files to comparing many small files, or a few medium-sized files, we need a more efficient approach. This is where signature generation comes into play.

To generate a signature, we must have a few...