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Cloud Forensics Demystified

You're reading from Cloud Forensics Demystified Decoding cloud investigation complexities for digital forensic professionals

Product type Paperback

Published in Feb 2024

Publisher Packt

ISBN-13 9781800564411

Length 384 pages

Edition 1st Edition

Tools

AWS

Concepts

Forensics

Authors (2):

Mansoor Haqanee

Ganesh Ramakrishnan

View More author details

Table of Contents (18) Chapters

Preface

1. Part 1: Cloud Fundamentals

2. Chapter 1: Introduction to the Cloud FREE CHAPTER

3. Chapter 2: Trends in Cyber and Privacy Laws and Their Impact on DFIR

4. Chapter 3: Exploring the Major Cloud Providers

5. Chapter 4: DFIR Investigations – Logs in AWS

6. Part 2: Forensic Readiness: Tools, Techniques, and Preparation for Cloud Forensics

7. Chapter 5: DFIR Investigations – Logs in Azure

8. Chapter 6: DFIR Investigations – Logs in GCP

9. Chapter 7: Cloud Productivity Suites

10. Part 3: Cloud Forensic Analysis – Responding to an Incident in the Cloud

11. Chapter 8: The Digital Forensics and Incident Response Process

12. Chapter 9: Common Attack Vectors and TTPs

13. Chapter 10: Cloud Evidence Acquisition

14. Chapter 11: Analyzing Compromised Containers

15. Chapter 12: Analyzing Compromised Cloud Productivity Suites

16. Index

Why subscribe?

17. Other Books You May Enjoy

Logging Dataflow pipelines

Dataflow pipelines provide a stream of data or batch processing capabilities at scale. GCP’s Dataflow pipeline is based on Apache Beam. Logs can be streamed at variable volumes in near real time using Dataflow applications.

Any actions performed on GCP Dataflow are recorded by default in Logs Explorer. Through Logs Explorer, investigators can detect any changes to the Dataflow parameters or whether unauthorized users altered the pipeline.

Note that a Docker instance forms the base of any Dataflow pipeline’s operations. Therefore, investigators must also investigate the logs emitted by the GKE cluster and GCE Instance Group Manager. GCP relies on Instance Group Manager to create multiple managed VMs that run the containers (GKE) to handle instance resourcing and deploying VMs automatically.

The following figure outlines some sample resources required for successful Dataflow pipeline execution. Like Syslog, Dataflow events are tagged...

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Authors (2)

Ramakrishnan

Ramakrishnan

Ganesh Ramakrishnan is a senior manager at KPMG Canada's Incident Response team, with over 12 years of incident response experience. He leads a dynamic team focused on responding to and managing incidents for organizations across various industry sectors, working with KPMG's incident response teams globally. He has led numerous incident response cases, including high-profile ones, and collaborated with law enforcement agencies worldwide. Apart from assisting organizations during crises, Ganesh also helps them prepare for incidents and educates them on handling them. Ganesh has a master's in computer application and an MSc in network and information security. He also holds CISSP, SANS GCFA, and SANS GNFA certifications.

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Haqanee

Haqanee

Mansoor Haqanee is a manager with KPMG Canada's Forensic Technology team, with over six years of experience in software development, computer forensics, and incident response. Mansoor has a background in electrical engineering with a bachelor of engineering from Toronto Metropolitan University (formerly Ryerson University). Combining his education with both software development and computer forensic experience, he is equipped to provide organizations with insights into the security of their assets. Mansoor has provided technology consulting services to a wide range of industries in the education, financial services, healthcare, telecommunications, manufacturing, and government sectors, to name a few.

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