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

Summary


E-mail files contain a large amount of valuable information, allowing forensic examiners to gain greater insight into communications and activity of users over time. Using open source libraries, we are able to explore PST files and extract information about the messages and folders within. We also examined the content and metadata of the messages to gather additional information about frequent contacts, common words, and abnormal hot spots of activity. Through this automated process, we can gather a better understanding of the data we review and begin to identify hidden trends. The code for this project can be downloaded from https://packtpub.com/books/content/support. Additional code to support the libpff installation can be found at http://github.com/PythonForensics/libpff.

Identifying hidden information is very important in all investigations, and is one of the many reasons that data recovery is an important cornerstone in the forensic investigation process. In the next chapter...