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Python Digital Forensics Cookbook

You're reading from   Python Digital Forensics Cookbook Effective Python recipes for digital investigations

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781783987467
Length 412 pages
Edition 1st Edition
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Authors (2):
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Chapin Bryce Chapin Bryce
Author Profile Icon Chapin Bryce
Chapin Bryce
Preston Miller Preston Miller
Author Profile Icon Preston Miller
Preston Miller
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Table of Contents (11) Chapters Close

Preface 1. Essential Scripting and File Information Recipes FREE CHAPTER 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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