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Learning Python for Forensics

You're reading from   Learning Python for Forensics Leverage the power of Python in forensic investigations

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789341690
Length 476 pages
Edition 2nd Edition
Languages
Concepts
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Authors (2):
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Preston Miller Preston Miller
Author Profile Icon Preston Miller
Preston Miller
Chapin Bryce Chapin Bryce
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Chapin Bryce
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Table of Contents (15) Chapters Close

Preface 1. Now for Something Completely Different FREE CHAPTER 2. Python Fundamentals 3. Parsing Text Files 4. Working with Serialized Data Structures 5. Databases in Python 6. Extracting Artifacts from Binary Files 7. Fuzzy Hashing 8. The Media Age 9. Uncovering Time 10. Rapidly Triaging Systems 11. Parsing Outlook PST Containers 12. Recovering Transient Database Records 13. Coming Full Circle 14. Other Books You May Enjoy

Parsing WAL files – wal_crawler.py

Now that we understand how a WAL file is structured and what data type we'll use to store data, we can begin planning the script. As we're working with a large binary object, we'll make great use of the struct library. We first introduced struct in Chapter 6, Extracting Artifacts from Binary Files, and have used it whenever dealing with binary files. Therefore, we won't repeat the basics of struct in this chapter.

The goal of our wal_crawler.py script is to parse the content of the WAL file, extract and write the cell content to a CSV file, and, optionally, run regular expression modules against the extracted data. This script is considered more advanced due to the complexity of the underlying object we're parsing. However, all we're doing here is applying what we've learned in the previous chapters at...

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