Table of Contents for
Python for Secret Agents

Version ebook / Retour

Cover image for bash Cookbook, 2nd Edition Python for Secret Agents by Steven F. Lott Published by Packt Publishing, 2014
  1. Cover
  2. Table of Contents
  3. Python for Secret Agents
  4. Python for Secret Agents
  5. Credits
  6. About the Author
  7. About the Reviewers
  8. www.PacktPub.com
  9. Preface
  10. What you need for this book
  11. Who this book is for
  12. Conventions
  13. Reader feedback
  14. Customer support
  15. 1. Our Espionage Toolkit
  16. Getting more tools – a text editor
  17. Confirming our tools
  18. Background briefing – math and numbers
  19. Handling text and strings
  20. Organizing our software
  21. Working with files and folders
  22. Solving problems – recovering a lost password
  23. Summary
  24. 2. Acquiring Intelligence Data
  25. Using a REST API in Python
  26. Organizing collections of data
  27. Solving problems – currency conversion rates
  28. Summary
  29. 3. Encoding Secret Messages with Steganography
  30. Using the Pillow library
  31. Some approaches to steganography
  32. Detecting and preventing tampering
  33. Solving problems – encrypting a message
  34. Summary
  35. 4. Drops, Hideouts, Meetups, and Lairs
  36. Finding out where we are with geocoding services
  37. How close? What direction?
  38. Compressing data to make grid codes
  39. Decoding a GeoRef code
  40. Creating natural area codes
  41. Solving problems – closest good restaurant
  42. Summary
  43. 5. A Spymaster's More Sensitive Analyses
  44. Creating Python modules and applications
  45. Creating our own classes of objects
  46. Comparisons and correlations
  47. Writing high-quality software
  48. Solving problems – analyzing some interesting datasets
  49. Summary
  50. Index

Preface

Every secret agent needs a good set of tools and gadgets. When an agent's missions involve gathering data, high-powered data processing is required. This book will provide you with the kinds of information processing tools that will help you gather, analyze, and communicate the data that the HQ demands.

Python allows agents to write simple scripts to gather data, perform sophisticated calculations, and produce useful results. Agents can also use Python to extract data from local files, HTTP web servers, and FTP file servers.

Python has numerous add-on packages. This book will explore just two: Pillow allows for sophisticated image conversion and manipulation, and BeautifulSoup allows an agent to extract data from HTML web pages. Agents with specific needs might have to explore the Python Natural Language Toolkit (NLTK), Numeric Python (NumPy), or even Scientific Python (SciPy).

What this book covers

Chapter 1, Our Espionage Toolkit, exposes the basics of installing and using Python. We'll write scripts to help agents work with foreign currency conversions and learn how an agent can recover a lost password from a ZIP archive.

Chapter 2, Acquiring Intelligence Data, shows how we can use Python to extract information from various kinds of file servers. Agents will learn how to work with different Internet protocols and use Representational State Transfer (REST) to interact with web services. This will include techniques to work with cyptocurrencies, such as bitcoins.

Chapter 3, Encoding Secret Messages with Steganography, shows how we can add the Pillow toolset to work with images. An agent with Pillow can create thumbnails and convert, crop, and enhance images. We'll also explore some steganography algorithms to bury our messages in an image file.

Chapter 4, Drops, Hideouts, Meetups, and Lairs, provides a closer look at geocoding and geolocation. This includes the use of web services to convert an address into a latitude and longitude. We'll also learn how to convert a latitude and longitude back into an address. We'll take a look at the haversine formula to get the correct distance between locations. We'll also look at some of the ways in which geographic locations can be represented for tidy storage and communication.

Chapter 5, A Spymaster's More Sensitive Analyses, shows how we can use Python for a basic data analysis. A good agent doesn't just spout facts and figures; a good agent does enough analysis to confirm that the data is realistic. Being able to examine the correlation between datasets is what creates a valuable intelligence asset.