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)

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, isn't processed. The challenge here is to add the newly discovered files to the current file listing.

We might do that by returning a list of newly discovered files back to metadata_parser.py. Another route might be to check...