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Python for Secret Agents

Author Steven F. Lott
Release Date: 2014/08/01
ISBN: 9781783980420
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Book Description

Analyze, encrypt, and uncover intelligence data using Python, the essential tool for all aspiring secret agents

In Detail

Python is an easy-to-learn and extensible programming language that allows secret agents to work with a wide variety of data in a number of ways. It gives beginners a simple way to start programming, but Python's standard library also provides numerous packages that allow Python-using secret agents to easily utilize very sophisticated information processing.

This book will guide new field agent trainees through putting together a Python-based toolset to gather, analyze, and communicate data. It starts by covering the basics and then moves on to sections such as file exchange, image processing, geocoding, simple trigonometry, and more sensitive statistical processing. You will then learn how to use polynomials to encode and decode data in different representations. Furthermore, this book shows you how to add tools to a Python environment, work with images, and parse HTML web pages to extract meaningful data. The idea of adding packages to Python is central to how an agent will leverage these tools for data processing.

What You Will Learn

  • Quickly get to grips with using Python to create tools and solve problems
  • Manipulate image files and learn how to encode messages into an image using steganography
  • Gather a file's hidden secrets, such as EXIF data and ZIP archive contents
  • Build applications that access, filter, and analyze live data from the Web
  • Design Python modules, libraries, and applications
  • Customize your Python environment with specialized packages
  • Extract data using HTTP and FTP internetworking protocols

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Table of Contents

  1. Python for Secret Agents
    1. Table of Contents
    2. Python for Secret Agents
    3. Credits
    4. About the Author
    5. About the Reviewers
    6. www.PacktPub.com
      1. Support files, eBooks, discount offers and more
        1. Why Subscribe?
        2. Free Access for Packt account holders
    7. Preface
      1. What this book covers
      2. What you need for this book
      3. Who this book is for
      4. Conventions
      5. Reader feedback
      6. Customer support
        1. Downloading the example code
        2. Errata
        3. Piracy
        4. Questions
    8. 1. Our Espionage Toolkit
      1. Getting the tools of the trade – Python 3.3
        1. Windows secrets
        2. Mac OS X secrets
      2. Getting more tools – a text editor
        1. Getting other developer tools
        2. Getting a tool to get more Python components
      3. Confirming our tools
        1. How do we stop?
        2. Using the help() system
          1. Mac OS and GNU/Linux secrets
          2. Windows secrets
        3. Using the help mode
      4. Background briefing – math and numbers
        1. The usual culprits
        2. The ivory tower of numbers
          1. Integer numbers
          2. Rational numbers
          3. Floating-point numbers
          4. Decimal numbers
          5. Complex numbers
        3. Outside the numbers
        4. Assigning values to variables
        5. Writing scripts and seeing output
        6. Gathering user input
          1. Handling exceptions
          2. Looping and trying again
      5. Handling text and strings
        1. Converting between numbers and strings
        2. Parsing strings
      6. Organizing our software
      7. Working with files and folders
        1. Creating a file
        2. Reading a file
        3. Defining more complex logical conditions
      8. Solving problems – recovering a lost password
        1. Reading a word corpus
        2. Reading a ZIP archive
        3. Using brute-force search
      9. Summary
    9. 2. Acquiring Intelligence Data
      1. Accessing data from the Internet
        1. Background briefing – the TCP/IP protocols
        2. Using http.client for HTTP GET
        3. Changing our client information
        4. Using FTP in Python
          1. Downloading a file via FTP
          2. Using our FTP get() function
        5. Using urllib for HTTP, FTP, or file access
        6. Using urllib for FTP access
      2. Using a REST API in Python
        1. Getting simple REST data
        2. Using more complex RESTful queries
        3. Saving our data via JSON
      3. Organizing collections of data
        1. Using a Python list
          1. Using list index operations
        2. Using a Python tuple
          1. Using generator expressions with list of tuples
        3. Using a Python dictionary mapping
          1. Using the dictionary access methods
        4. Transforming sequences with generator functions
        5. Using the defaultdict and counter mappings
        6. Using a Python set
        7. Using the for statement with a collection
        8. Using Python operators on collections
      4. Solving problems – currency conversion rates
      5. Summary
    10. 3. Encoding Secret Messages with Steganography
      1. Background briefing – handling file formats
        1. Working with the OS filesystem
          1. glob
          2. os
        2. Processing simple text files
        3. Working with ZIP files
        4. Working with JSON files
        5. Working with CSV files
        6. JPEG and PNG graphics – pixels and metadata
      2. Using the Pillow library
        1. Adding the required supporting libraries
          1. GNU/Linux secrets
          2. Mac OS X secrets
          3. Windows secrets
        2. Installing and confirming Pillow
        3. Decoding and encoding image data
        4. Manipulating images – resizing and thumbnails
        5. Manipulating images – cropping
        6. Manipulating images – enhancing
        7. Manipulating images – filtering
        8. Manipulating images – ImageOps
      3. Some approaches to steganography
        1. Getting the red-channel data
        2. Extracting bytes from Unicode characters
        3. Manipulating bits and bytes
        4. Assembling the bits
        5. Encoding the message
        6. Decoding a message
      4. Detecting and preventing tampering
        1. Using hash totals to validate a file
        2. Using a key with a digest
      5. Solving problems – encrypting a message
        1. Unpacking a message
      6. Summary
    11. 4. Drops, Hideouts, Meetups, and Lairs
      1. Background briefing – latitude, longitude, and GPS
        1. Coping with GPS device limitations
        2. Handling politics – borders, precincts, jurisdictions, and neighborhoods
      2. Finding out where we are with geocoding services
        1. Geocoding an address
        2. Reverse geocoding a latitude-longitude point
      3. How close? What direction?
        1. Combining geocoding and haversine
      4. Compressing data to make grid codes
        1. Creating GeoRef codes
      5. Decoding a GeoRef code
        1. Creating Maidenhead grid codes
        2. Decoding the Maidenhead grid codes
      6. Creating natural area codes
        1. Decoding natural area codes
      7. Solving problems – closest good restaurant
        1. Creating simple Python objects
        2. Working with HTML web services – tools
        3. Working with HTML web services – getting the page
        4. Working with HTML web services – parsing a table
        5. Making a simple Python object from columns of data
        6. Enriching Python objects with geocodes
        7. Enriching Python objects with health scores
        8. Combining the pieces and parts
        9. Working with clean data portals
        10. Making a simple Python object from a JSON document
        11. Combining different pieces and parts
        12. Final steps
        13. Understanding the data – schema and metadata
      8. Summary
    12. 5. A Spymaster's More Sensitive Analyses
      1. Creating statistical summaries
        1. Parsing the raw data file
        2. Finding an average value
          1. Understanding generator expressions
        3. Finding the value in the middle
        4. Finding the most popular value
      2. Creating Python modules and applications
        1. Creating and using a module
        2. Creating an application module
        3. Creating a hybrid module
      3. Creating our own classes of objects
        1. Using a class definition
      4. Comparisons and correlations
        1. Computing the standard deviation
        2. Computing a standardized score
          1. Comparing a sequence and an iterable
        3. Computing a coefficient of correlation
      5. Writing high-quality software
        1. Building a self-testing module and a test module
        2. Creating more sophisticated tests
        3. Adding doctest cases to a class definition
      6. Solving problems – analyzing some interesting datasets
        1. Getting some more data
        2. Further research
      7. Summary
    13. Index
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