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Learning Python for Forensics

You're reading from   Learning Python for Forensics Learn the art of designing, developing, and deploying innovative forensic solutions through Python

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Product type Paperback
Published in May 2016
Last Updated in Feb 2025
Publisher Packt
ISBN-13 9781783285235
Length 488 pages
Edition 1st Edition
Languages
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Authors (2):
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 Miller Miller
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Miller
Chapin Bryce Chapin Bryce
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Table of Contents (18) 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. Did Someone Say Keylogger? 11. Parsing Outlook PST Containers 12. Recovering Transient Database Records 13. Coming Full Circle A. Installing Python B. Python Technical Details
C. Troubleshooting Exceptions Index

Parsing WAL files – wal_crawler.py

Now that we understand how a WAL file is structured and what datatype we will use to store data, we can begin planning the script. As we are working with a large binary object, we will 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 and will not 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 have learned in the previous chapters on a larger scale.

001 import argparse
002 import binascii
003 import csv
004 import logging
005 import os
006 import re
007 import struct
008...
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