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

Advanced data types and functions


This section highlights two common features of Python that we will frequently encounter in forensic scripts. Therefore, we will introduce these objects and functionality in great detail.

Iterators

You have previously learned several iterable objects, such as lists, sets, and tuples. In Python, a data type is considered an iterator if an __iter__ method is defined or elements can be accessed using indices. These three data types (that is, lists, sets, and tuples) allow us to iterate through their contents in a simple and efficient manner. For this reason, we often use these data types when iterating through the lines in a file, file entries within a directory listing, or trying to identify a file based on a series of file signatures.

The iter data type allows us to step through data in a manner that doesn't preserve the initial object. This seems undesirable; however, when working with large sets or on machines with limited resources, it is very useful. This...