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  • Book Overview & Buying Learning Python for Forensics
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Learning Python for Forensics

Learning Python for Forensics

By : Preston Miller, Chapin Bryce
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Learning Python for Forensics

Learning Python for Forensics

5 (4)
By: Preston Miller, 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 (18 chapters)
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15
B. Python Technical Details
17
Index

Summary


In this chapter, we covered how to convert between machine- and human-readable timestamps and display that information in GUI. The primary goal of a forensic developer is to be capable of facilitating rapid design and deployment of tools that provide insight into investigations. However, in this chapter, we focused a bit more on the end user by spending a little extra time to build a nice interface for the user to operate and interact with. The code for this project can be downloaded from https://packtpub.com/books/content/support.

In the next chapter, we will learn how to create a keylogger by calling Windows-specific APIs. While, typically, we do not develop our own "hacking" tools, it is a useful exercise in identifying how the "suspect" can use Python to their advantage. It will also provide an opportunity to learn new Python libraries that are specific to the Windows operating system and are highly useful for all Python developers and not just those with ill intent.

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