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)

Getting a jump start with IEF

Recipe Difficulty: Easy

Python Version: 3.5

Operating System: Any

This recipe will act as a quick means of dumping all reports from IEF to a CSV file and an introduction to interacting with IEF results. IEF stores data in a SQLite database, which we explored rather thoroughly in Chapter 3, A Deep Dive into Mobile Forensic Recipes. As IEF can be configured to scan specific categories of information, it is not so simple as dumping out set tables for each IEF database. Instead, we must determine this information dynamically and then interact with said tables. This recipe will dynamically identify result tables within the IEF database and dump them to respective CSV files. This process can be performed on any SQLite database to quickly dump its contents to a CSV file for review.

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