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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

Going spelunking

Recipe Difficulty: Medium

Python Version: 2.7

Operating System: Any

Log files can quickly become quite sizable due to the level of detail and time frame preserved. As you may have noticed, the CSV report from the prior recipe can easily become too large for our spreadsheet application to open or browse efficiently. Rather than analyzing this data in a spreadsheet, one alternative would be to load the data into a database.

Splunk is a platform that incorporates a NoSQL database with an ingestion and query engine, making it a powerful analysis tool. Its database operates in a manner like Elasticsearch or MongoDB, permitting the storage of documents or structured records. Because of this, we do not need to provide records with a consistent key-value mapping to store them in the database. This is what makes NoSQL databases so useful for log analysis, as log formats...

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