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Python Digital Forensics Cookbook: Effective Python recipes for digital investigations
Key FeaturesDevelop 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.Book DescriptionTechnology 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.
What you will learnUnderstand how Python can enhance digital forensics and investigationsLearn to access the contents of, and process, forensic evidence containersExplore malware through automated static analysisExtract and review message contents from a variety of email formatsAdd 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 databasesIndex large logs into a platform to better query and visualize datasetsAbout the AuthorPreston Miller is a consultant at an internationally recognized risk management firm. He holds an undergraduate degree from Vassar College and a master's degree in Digital Forensics from Marshall University. While at Marshall, Preston unanimously received the prestigious J. Edgar Hoover Foundation's Scientific Scholarship. He is a published author, recently of Learning Python for Forensics, an introductory Python Forensics textbook. Preston is also a member of the GIAC advisory board and holds multiple industry-recognized certifications in his field.
Chapin Bryce works as a consultant in digital forensics, focusing on litigation support, incident response, and intellectual property investigations. After studying computer and digital forensics at Champlain College, he joined a firm leading the field of digital forensics and investigations. In his downtime, Chapin enjoys working on side projects, hiking, and skiing (if the weather permits). As a member of multiple ongoing research and development projects, he has authored several articles in professional and academic publications.
Table of ContentsWorking with System/File Info A Deep Dive into Mobile Forensics Extracting Embedded Metadata Exploring Networking and Indicators of Compromise Reading Emails and Taking Names Forensic Evidence Log Based Artifacts Exploring Windows Forensic Artifact Exploring Windows Forensic Artifact
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.
What you will learnUnderstand how Python can enhance digital forensics and investigationsLearn to access the contents of, and process, forensic evidence containersExplore malware through automated static analysisExtract and review message contents from a variety of email formatsAdd 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 databasesIndex large logs into a platform to better query and visualize datasetsAbout the AuthorPreston Miller is a consultant at an internationally recognized risk management firm. He holds an undergraduate degree from Vassar College and a master's degree in Digital Forensics from Marshall University. While at Marshall, Preston unanimously received the prestigious J. Edgar Hoover Foundation's Scientific Scholarship. He is a published author, recently of Learning Python for Forensics, an introductory Python Forensics textbook. Preston is also a member of the GIAC advisory board and holds multiple industry-recognized certifications in his field.
Chapin Bryce works as a consultant in digital forensics, focusing on litigation support, incident response, and intellectual property investigations. After studying computer and digital forensics at Champlain College, he joined a firm leading the field of digital forensics and investigations. In his downtime, Chapin enjoys working on side projects, hiking, and skiing (if the weather permits). As a member of multiple ongoing research and development projects, he has authored several articles in professional and academic publications.
Table of ContentsWorking with System/File Info A Deep Dive into Mobile Forensics Extracting Embedded Metadata Exploring Networking and Indicators of Compromise Reading Emails and Taking Names Forensic Evidence Log Based Artifacts Exploring Windows Forensic Artifact Exploring Windows Forensic Artifact
800 pages, Kindle Edition
Published September 26, 2017
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April 7, 2018
Many interesting recipes to extend your Python skills. This will not teach you Python, but it should help you take your Python coding skills to the next level by introducing many Python modules/libraries that are useful for forensics. Almost every chapter gave me a little something that I immediately applied to improving one of my existing scripts.
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