Python Digital Forensics Cookbook
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Python Digital Forensics Cookbook
Author: Preston Miller
language: en
Publisher: Packt Publishing Ltd
Release Date: 2017-09-26
Over 60 recipes to help you learn digital forensics and leverage Python scripts to amplify your examinations About This Book Develop code that extracts vital information from everyday forensic acquisitions. Increase the quality and efficiency of your forensic analysis. Leverage the latest resources and capabilities available to the forensic community. Who This Book Is For If you are a digital forensics examiner, cyber security specialist, or analyst at heart, understand the basics of Python, and want to take it to the next level, this is the book for you. Along the way, you will be introduced to a number of libraries suitable for parsing forensic artifacts. Readers will be able to use and build upon the scripts we develop to elevate their analysis. What You Will Learn Understand how Python can enhance digital forensics and investigations Learn to access the contents of, and process, forensic evidence containers Explore malware through automated static analysis Extract and review message contents from a variety of email formats Add depth and context to discovered IP addresses and domains through various Application Program Interfaces (APIs) Delve into mobile forensics and recover deleted messages from SQLite databases Index large logs into a platform to better query and visualize datasets In Detail Technology plays an increasingly large role in our daily lives and shows no sign of stopping. Now, more than ever, it is paramount that an investigator develops programming expertise to deal with increasingly large datasets. By leveraging the Python recipes explored throughout this book, we make the complex simple, quickly extracting relevant information from large datasets. You will explore, develop, and deploy Python code and libraries to provide meaningful results that can be immediately applied to your investigations. Throughout the Python Digital Forensics Cookbook, recipes include topics such as working with forensic evidence containers, parsing mobile and desktop operating system artifacts, extracting embedded metadata from documents and executables, and identifying indicators of compromise. You will also learn to integrate scripts with Application Program Interfaces (APIs) such as VirusTotal and PassiveTotal, and tools such as Axiom, Cellebrite, and EnCase. By the end of the book, you will have a sound understanding of Python and how you can use it to process artifacts in your investigations. Style and approach Our succinct recipes take a no-frills approach to solving common challenges faced in investigations. The code in this book covers a wide range of artifacts and data sources. These examples will help improve the accuracy and efficiency of your analysis—no matter the situation.
Python Digital Forensics Cookbook
Over 60 recipes to help you learn digital forensics and leverage Python scripts to amplify your examinationsAbout This Book* Develop code that extracts vital information from everyday forensic acquisitions.* Increase the quality and efficiency of your forensic analysis.* Leverage the latest resources and capabilities available to the forensic community.Who This Book Is ForIf you are a digital forensics examiner, cyber security specialist, or analyst at heart, understand the basics of Python, and want to take it to the next level, this is the book for you. Along the way, you will be introduced to a number of libraries suitable for parsing forensic artifacts. Readers will be able to use and build upon the scripts we develop to elevate their analysis.What You Will Learn* Understand how Python can enhance digital forensics and investigations* Learn to access the contents of, and process, forensic evidence containers* Explore malware through automated static analysis* Extract and review message contents from a variety of email formats* Add depth and context to discovered IP addresses and domains through various Application Program Interfaces (APIs)* Delve into mobile forensics and recover deleted messages from SQLite databases* Index large logs into a platform to better query and visualize datasetsIn DetailTechnology plays an increasingly large role in our daily lives and shows no sign of stopping. Now, more than ever, it is paramount that an investigator develops programming expertise to deal with increasingly large datasets.By leveraging the Python recipes explored throughout this book, we make the complex simple, quickly extracting relevant information from large datasets. You will explore, develop, and deploy Python code and libraries to provide meaningful results that can be immediately applied to your investigations. Throughout the Python Digital Forensics Cookbook, recipes include topics such as working with forensic evidence containers, parsing mobile and desktop operating system artifacts, extracting embedded metadata from documents and executables, and identifying indicators of compromise. You will also learn to integrate scripts with Application Program Interfaces (APIs) such as VirusTotal and PassiveTotal, and tools such as Axiom, Cellebrite, and EnCase.By the end of the book, you will have a sound understanding of Python and how you can use it to process artifacts in your investigations.Style and approachOur succinct recipes take a no-frills approach to solving common challenges faced in investigations. The code in this book covers a wide range of artifacts and data sources. These examples will help improve the accuracy and efficiency of your analysis-no matter the situation.
Learning Python for Forensics
Author: Preston Miller
language: en
Publisher: Packt Publishing Ltd
Release Date: 2019-01-31
Design, develop, and deploy innovative forensic solutions using Python Key FeaturesDiscover how to develop Python scripts for effective digital forensic analysisMaster the skills of parsing complex data structures with Python librariesSolve forensic challenges through the development of practical Python scriptsBook Description Digital forensics plays an integral role in solving complex cybercrimes and helping organizations make sense of cybersecurity incidents. This second edition of Learning Python for Forensics illustrates how Python can be used to support these digital investigations and permits the examiner to automate the parsing of forensic artifacts to spend more time examining actionable data. The second edition of Learning Python for Forensics will illustrate how to develop Python scripts using an iterative design. Further, it demonstrates how to leverage the various built-in and community-sourced forensics scripts and libraries available for Python today. This book will help strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. By the end of this book, you will build a collection of Python scripts capable of investigating an array of forensic artifacts and master the skills of extracting metadata and parsing complex data structures into actionable reports. Most importantly, you will have developed a foundation upon which to build as you continue to learn Python and enhance your efficacy as an investigator. What you will learnLearn how to develop Python scripts to solve complex forensic problemsBuild scripts using an iterative designDesign code to accommodate present and future hurdlesLeverage built-in and community-sourced librariesUnderstand the best practices in forensic programmingLearn how to transform raw data into customized reports and visualizationsCreate forensic frameworks to automate analysis of multiple forensic artifactsConduct effective and efficient investigations through programmatic processingWho this book is for If you are a forensics student, hobbyist, or professional seeking to increase your understanding in forensics through the use of a programming language, then Learning Python for Forensics is for you. You are not required to have previous experience in programming to learn and master the content within this book. This material, created by forensic professionals, was written with a unique perspective and understanding for examiners who wish to learn programming.