Book Image

Learning Python for Forensics

By : Chapin Bryce
Book Image

Learning Python for Forensics

By: Chapin Bryce

Overview of this book

This book will illustrate how and why you should learn Python to strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. The tutorials use an interactive design, giving you experience of the development process so you gain a better understanding of what it means to be a forensic developer. Each chapter walks you through a forensic artifact and one or more methods to analyze the evidence. It also provides reasons why one method may be advantageous over another. We cover common digital forensics and incident response scenarios, with scripts that can be used to tackle case work in the field. Using built-in and community-sourced libraries, you will improve your problem solving skills with the addition of the Python scripting language. In addition, we provide resources for further exploration of each script so you can understand what further purposes Python can serve. With this knowledge, you can rapidly develop and deploy solutions to identify critical information and fine-tune your skill set as an examiner.
Table of Contents (24 chapters)
Learning Python for Forensics
Credits
About the Authors
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Index

Chapter 6. Extracting Artifacts from Binary Files

Parsing binary data is an indispensable skill. Inevitably, we are tasked with analyzing artifacts that are unfamiliar or undocumented. This issue is compounded when the file of interest is a binary file. Rather than analyzing a text-like file, we need to use our favorite hex editor to begin reverse engineering the file's internal binary structure. Reverse engineering the underlying logic of binary files is out of scope for this chapter. Instead, we will work with a binary object whose structure is already well known. This will allow us to highlight how to use Python to parse these binary structures automatically once the internal structure is understood. In this chapter, we will examine the UserAssist registry key from the NTUSER.DAT registry hive.

This chapter illustrates how to extract Python objects from binary data and generate an automatic Excel report. We will use three modules to accomplish this task: struct, Registry, and xlsxwriter...