Python Forensics provides many never-before-published proven forensic modules, libraries, and solutions that can be used right out of the box. In addition, detailed instruction and documentation provided with the code samples will allow even novice Python programmers to add their own unique twists or use the models presented to build new solutions.

Rapid development of new cybercrime investigation tools is an essential ingredient in virtually every case and environment. Whether you are performing post-mortem investigation, executing live triage, extracting evidence from mobile devices or cloud services, or you are collecting and processing evidence from a network, Python forensic implementations can fill in the gaps.

Drawing upon years of practical experience and using numerous examples and illustrative code samples, author Chet Hosmer discusses how to:
Develop new forensic solutions independent of large vendor software release schedules Participate in an open-source workbench that facilitates direct involvement in the design and implementation of new methods that augment or replace existing tools Advance your career by creating new solutions along with the construction of cutting-edge automation solutions to solve old problemsProvides hands-on tools, code samples, and detailed instruction and documentation that can be put to use immediatelyDiscusses how to create a Python forensics workbenchCovers effective forensic searching and indexing using PythonShows how to use Python to examine mobile device operating systems: iOS, Android, and Windows 8 Presents complete coverage of how to use Python scripts for network investigation


Table of contents :
Content:
Front Matter, Pages i-ii
Copyright, Page iv
Dedication, Page v
Acknowledgments, Page vii
Endorsements, Pages ix-x
List of figures, Pages xvii-xx
About the Author, Page xxi
About the Technical Editor, Page xxiii
Foreword, Page xxv
Preface, Pages xxvii-xxviii
Chapter 1 - Why Python Forensics?, Pages 1-11
Chapter 2 - Setting up a Python Forensics Environment, Pages 13-52
Chapter 3 - Our First Python Forensics App, Pages 53-89
Chapter 4 - Forensic Searching and Indexing Using Python, Pages 91-123
Chapter 5 - Forensic Evidence Extraction (JPEG and TIFF), Pages 125-163
Chapter 6 - Forensic Time, Pages 165-181
Chapter 7 - Using Natural Language Tools in Forensics, Pages 183-203
Chapter 8 - Network Forensics: Part I, Pages 205-235
Chapter 9 - Network Forensics: Part II, Pages 237-263
Chapter 10 - Multiprocessing for Forensics, Pages 265-288
Chapter 11 - Rainbow in the Cloud, Pages 289-303
Chapter 12 - Looking Ahead, Pages 305-312
Index, Pages 313-318