Book Image

Python Digital Forensics Cookbook

By : Chapin Bryce, Preston Miller
Book Image

Python Digital Forensics Cookbook

By: Chapin Bryce, Preston Miller

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)

Introduction

These days it is not uncommon to encounter modern systems equipped with some form of event or activity monitoring software. This software may be implemented to assist with security, debugging, or compliance requirements. Whatever the situation, this veritable treasure trove of information can be, and commonly is, leveraged in all types of cyber investigations. A common issue with log analysis can be the huge amount of data one is required to sift through for the subset of interest. Through the recipes in this chapter, we will explore various logs with great evidentiary value and demonstrate ways to quickly process and review them. Specifically, we will cover:

  • Converting different timestamp formats (UNIX, FILETIME, and so on) to human-readable formats
  • Parsing web server access logs from an IIS platform
  • Ingesting, querying, and exporting logs with Splunk's Python...