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 12. Recovering Transient Database Records

In this chapter, we will revisit SQLite databases and examine a type of "journaling" file called a Write Ahead Log (WAL). Parsing a WAL file, due to the complexity of the underlying structure, makes this a more difficult task than our previous encounter with SQLite databases. There are no existing modules we can leverage to directly interact with the WAL file in the same way we used sqlite3 or peewee with SQLite databases. Instead, we will rely on the struct library and our ability to understand binary files.

Once we have successfully parsed the WAL file, we will leverage the re regular expression library in Python to identify potentially relevant forensic artifacts. Lastly, we will briefly introduce another method of creating progress bars using the third-party tqdm library. In a few lines of code, we will have a functioning progress bar that can provide feedback of program execution to the user.

The WAL file can contain data that is no longer...