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Python digital forensics cookbook : effective Python recipes for digital investigations /
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing,
2017.
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| Temas: | |
| Acceso en línea: | Texto completo Texto completo |
MARC
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| 100 | 1 | |a Miller, Preston, |e author. | |
| 245 | 1 | 0 | |a Python digital forensics cookbook : |b effective Python recipes for digital investigations / |c Preston Miller, Chapin Bryce. |
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| 520 | |a 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- ... | ||
| 505 | 0 | |a Python digital forensics cookbook : effective Python recipes for digital investigations -- Credits -- About the Authors -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- 1: Essential Scripting and File Information Recipes -- 2: Creating Artifact Report Recipes -- 3: A Deep Dive into Mobile Forensic Recipes -- 4: Extracting Embedded Metadata Recipes -- 5: Networking and Indicators of Compromise Recipes -- 6: Reading Emails and Taking Names Recipes -- 7: Log-Based Artifact Recipes -- 8: Working with Forensic Evidence Container Recipes -- 9: Exploring Windows Forensic Artifacts Recipes -- Part I -- 10: Exploring Windows Forensic Artifacts Recipes -- Part II -- Index. | |
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| 650 | 0 | |a Computer crimes |x Investigation. | |
| 650 | 0 | |a Forensic sciences |x Data processing. | |
| 650 | 0 | |a Python (Computer program language) | |
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| 650 | 6 | |a Criminalistique |x Informatique. | |
| 650 | 6 | |a Python (Langage de programmation) | |
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| 650 | 7 | |a Forensic sciences |x Data processing. |2 fast |0 (OCoLC)fst00932012 | |
| 650 | 7 | |a Python (Computer program language) |2 fast |0 (OCoLC)fst01084736 | |
| 700 | 1 | |a Bryce, Chapin, |e author. | |
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