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Python Digital Forensics Cookbook

You're reading from  Python Digital Forensics Cookbook

Product type Book
Published in Sep 2017
Publisher Packt
ISBN-13 9781783987467
Pages 412 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Chapin Bryce Chapin Bryce
Profile icon Chapin Bryce
Preston Miller Preston Miller
Profile icon Preston Miller
View More author details

Table of Contents (11) Chapters

Preface 1. Essential Scripting and File Information Recipes 2. Creating Artifact Report Recipes 3. A Deep Dive into Mobile Forensic Recipes 4. Extracting Embedded Metadata Recipes 5. Networking and Indicators of Compromise Recipes 6. Reading Emails and Taking Names Recipes 7. Log-Based Artifact Recipes 8. Working with Forensic Evidence Container Recipes 9. Exploring Windows Forensic Artifacts Recipes - Part I 10. Exploring Windows Forensic Artifacts Recipes - Part II

Digging deep to recover messages

Recipe Difficulty: Hard

Python Version: 3.5

Operating System: Any

Earlier in this chapter, we developed a recipe to identify missing records from a database. In this recipe, we will leverage the output from that recipe and identify recoverable records and their offset within a database. This is accomplished by understanding some internals of SQLite databases and leveraging that understanding to our advantage.

For a detailed description of the SQLite file internals, review https://www.sqlite.org/fileformat.html.

With this technique, we will be able to quickly triage a database and identify recoverable messages.

When a row from a database is deleted, similar to a file, the entry is not necessarily overwritten. This entry can still persist for some time based on database activity and its allocation algorithms. Our chances for data recovery decrease...

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