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

Additional challenges


We had difficulties deciding between two main challenges for this chapter. We could add additional plugins or refine what currently exists. In actual development, your time would be spent balancing these two objectives as the framework continues to grow. For this chapter, we propose a recursive-based challenge.

Remember that while explaining the post Office 2007 format of documents, we determined that attached media is stored in the media subdirectory of the document. In its current incarnation, when an Office document is encountered, that media subdirectory, which might have copies of files containing embedded metadata themselves, is not processed. The challenge here is to add the newly discovered files to the current file listing.

One might do that by returning a list of newly discovered files back to metadata_parser.py. Another route might be to check the file extensions in the office_parser.py script and pass them immediately onto the appropriate plugins. The latter...