The following recipes are covered in this chapter:
- About time
- Parsing IIS weblogs with RegEx
- Going spelunking
- Interpreting the daily out log
- Adding daily.out parsing to Axiom
- Scanning for indicators with YARA
Python Digital Forensics Cookbook
By :
Python Digital Forensics Cookbook
By:
Overview of this book
Technology plays an increasingly large role in our daily lives and shows no sign of stopping. Now, more than ever, it is paramount that an investigator develops programming expertise to deal with increasingly large datasets.
By leveraging the Python recipes explored throughout this book, we make the complex simple, quickly extracting relevant information from large datasets. You will explore, develop, and deploy Python code and libraries to provide meaningful results that can be immediately applied to your investigations. Throughout the Python Digital Forensics Cookbook, recipes include topics such as working with forensic evidence containers, parsing mobile and desktop operating system artifacts, extracting embedded metadata
from documents and executables, and identifying indicators of compromise. You
will also learn to integrate scripts with Application Program Interfaces (APIs) such
as VirusTotal and PassiveTotal, and tools such as Axiom, Cellebrite, and EnCase.
By the end of the book, you will have a sound understanding of Python and how you can use it to process artifacts in your investigations.
Table of Contents (11 chapters)
Preface
Free Chapter
Essential Scripting and File Information Recipes
Creating Artifact Report Recipes
A Deep Dive into Mobile Forensic Recipes
Extracting Embedded Metadata Recipes
Networking and Indicators of Compromise Recipes
Reading Emails and Taking Names Recipes
Log-Based Artifact Recipes
Working with Forensic Evidence Container Recipes
Exploring Windows Forensic Artifacts Recipes - Part I
Exploring Windows Forensic Artifacts Recipes - Part II
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