Book Image

Mastering Python Forensics

Book Image

Mastering Python Forensics

Overview of this book

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.

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Mastering Python Forensics
Oct, 2015 | 192 pages
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Table of Contents (14 chapters)
Mastering Python Forensics
Mastering Python Forensics
Credits
Credits
About the Authors
About the Authors
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Setting Up the Lab and Introduction to Python ctypes
Setting Up the Lab and Introduction to Python ctypes
Setting up the Lab
Introduction to Python ctypes
Summary
2
Forensic Algorithms
Forensic Algorithms
Algorithms
Supporting the chain of custody
Real-world scenarios
Summary
3
Using Python for Windows and Linux Forensics
Using Python for Windows and Linux Forensics
Analyzing the Windows Event Log
Analyzing the Windows Registry
Implementing Linux specific checks
Summary
4
Using Python for Network Forensics
Using Python for Network Forensics
Using Dshell during an investigation
Using Scapy during an investigation
Summary
5
Using Python for Virtualization Forensics
Using Python for Virtualization Forensics
Considering virtualization as a new attack surface
Searching for misuse of virtual resources
Using virtualization as a source of evidence
Summary
6
Using Python for Mobile Forensics
Using Python for Mobile Forensics
The investigative model for smartphones
Android
Apple iOS
Summary
7
Using Python for Memory Forensics
Using Python for Memory Forensics
Understanding Volatility basics
Using Volatility on Android
Using Volatility on Linux
Summary
Where to go from here
Index
Index

Summary

In this chapter, we provided an overview of memory forensics using the Volatility framework. In the examples, we demonstrated memory acquisition techniques for Android and Linux systems and saw how to use LiME on both systems. We used Volatility to get information about running processes, loaded modules, possibly malicious activity, and recent network activity. The latter is useful to trace the activities of an attacker through the network.

In the last example in this chapter, we demonstrated how to search for a given malware signature or other highly flexible pattern-based rules in such a memory dump. These YARA signatures or rules help in identifying suspicious activities or files really fast.

Furthermore, we demonstrated how to get the keyboard cache as well as call history from an Android device.

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