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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
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Authors (2):
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 Miller Miller
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Miller
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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

Using SSDeep in Python – ssdeep_python.py


In this second example of fuzzy hashing, we are going to implement a similar script using the ssdeep (version 3.1.1) Python library. This allows us to leverage the ssdeep tool and the Spamsum algorithm that have been widely used and accepted in the fields of digital forensics and information security. This code will be the preferred method for fuzzy hashing in most scenarios as it is more efficient with resources and produces more accurate results. This tool has seen wide support in the community, and many ssdeep signatures are available online. For example, the website http://VirusTotal.com hosts hashes from ssdeep on their site under additional information for submitted files. This public information can be used to check for known malicious files that match or are similar to executable files on a host machine without the need to download the malicious files.

One weakness of ssdeep is that it does not provide information beyond the matching percentage...

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