Mastering Python Forensics: Master the art of digital forensics and analysis with Python

NZ$36.99 ~~NZ$52.99~~

4.4 (7 Ratings)

eBook Oct 2015 192 pages 1st Edition

eBook

NZ$36.99 ~~NZ$52.99~~

NZ$36.99 ~~NZ$52.99~~

4.4 (7 Ratings)

eBook Oct 2015 192 pages 1st Edition

eBook

NZ$36.99 ~~NZ$52.99~~

NZ$36.99 ~~NZ$52.99~~

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Key benefits

Learn to perform forensic analysis and investigations with the help of Python, and gain an advanced understanding of the various Python libraries and frameworks
Analyze Python scripts to extract metadata and investigate forensic artifacts
The writers, Dr. Michael Spreitzenbarth and Dr. Johann Uhrmann, have used their experience to craft this hands-on guide to using Python for forensic analysis and investigations

Description

Digital forensic analysis is the process of examining and extracting data digitally and examining it. Python has the combination of power, expressiveness, and ease of use that makes it an essential complementary tool to the traditional, off-the-shelf digital forensic tools. This book will teach you how to perform forensic analysis and investigations by exploring the capabilities of various Python libraries. The book starts by explaining the building blocks of the Python programming language, especially ctypes in-depth, along with how to automate typical tasks in file system analysis, common correlation tasks to discover anomalies, as well as templates for investigations. Next, we’ll show you cryptographic algorithms that can be used during forensic investigations to check for known files or to compare suspicious files with online services such as VirusTotal or Mobile-Sandbox. Moving on, you’ll learn how to sniff on the network, generate and analyze network flows, and perform log correlation with the help of Python scripts and tools. You’ll get to know about the concepts of virtualization and how virtualization influences IT forensics, and you’ll discover how to perform forensic analysis of a jailbroken/rooted mobile device that is based on iOS or Android. Finally, the book teaches you how to analyze volatile memory and search for known malware samples based on YARA rules.

Who is this book for?

If you are a network security professional or forensics analyst who wants to gain a deeper understanding of performing forensic analysis with Python, then this book is for you. Some Python experience would be helpful.

What you will learn

Explore the forensic analysis of different platforms such as Windows, Android, and vSphere
Semi-automatically reconstruct major parts of the system activity and time-line
Leverage Python ctypes for protocol decoding
Examine artifacts from mobile, Skype, and browsers
Discover how to utilize Python to improve the focus of your analysis
Investigate in volatile memory with the help of volatility on the Android and Linux platforms

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

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Yves Vandermeer Dec 14, 2015

I enjoyed to link the topics covered using fully python scripting oriented approach developed in this book.However, you already need to have experience in computer forensics and understand main concepts to be able to implement provided methods. Python learning curve is outstanding fast and most of the readers will be able to address common forensics, including mobile forensics cases by only applying provided scripts and referenced libraries.As for all python books, tutorials and available code, the reader will have to, when feeling confortable with provided code, adapt the code to his own needs. Now that The Sleuthkit provides python modules, and with help of the covered C-types, forensics practitioners will have a real added value toolset to solve ad-hoc challenges.

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Denver Water - Dawson Mar 04, 2016

Wonderful published book. Great vendor!!

ruben Dec 26, 2015

The book starts by explaining the building blocks of the Python programming language, especially ctypes in-depth, along with how to automate typical tasks in file system analysis, common correlation tasks to discover anomalies, as well as templates for investigations. Next, we’ll show you cryptographic algorithms that can be used during forensic investigations to check for known files or to compare suspicious files with online services such as VirusTotal or Mobile-Sandbox.I have seen this book very interesting, and never seens it before, with this title helprs to comprenhen the main thing this Python Forensics.We can develop many things with this kind of information that I can have with this book. in may area I can apply these all kind of topics in networking areas.Ruben.

SuJo Dec 25, 2015

This book covers a lot of various topics when it comes to forensics, most importantly it covers mobile forensics which is something that is going to increase over time as phones become more robust. I'm very happy with the purchase and right now packt has a $5 book sale on all of their titles which makes it a no brainier, so head over to their main site for your purchase if you're buying this book right now. My favorite part about the book was sniffing network traffic, and I felt the YARA rules were covered quite well.While I agree with other reviews that you'll not master everything related to Python Forensics; however you will have a solid understanding and foundation to build upon.

Perry Nally Dec 27, 2015

If you need to know details about processes and how to extract data from hard drives or mobile devices this is the book for you. Though the Android tutorial uses Android 4.4.4 you can still use the walk through using the latest version. This is a useful book with a lot of great information and python scripts. He also tells you how to setup you environment in order to perform the data acquisitions and analysis to obtain sensitive data. Everyone dealing in digital forensics should read this book and have it as a reference manual. Great job!

Mastering Python Forensics: Master the art of digital forensics and analysis with Python

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