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Incident Response for Windows

You're reading from Incident Response for Windows Adapt effective strategies for managing sophisticated cyberattacks targeting Windows systems

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781804619322

Length 244 pages

Edition 1st Edition

Concepts

Cybersecurity

Authors (2):

Anatoly Tykushin

Svetlana Ostrovskaya

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Table of Contents (20) Chapters

Preface

1. Part 1: Understanding the Threat Landscape and Attack Life Cycle

2. Chapter 1: Introduction to the Threat Landscape FREE CHAPTER

3. Chapter 2: Understanding the Attack Life Cycle

4. Part 2: Incident Response Procedures and Endpoint Forensic Evidence Collection

5. Chapter 3: Phases of an Efficient Incident Response on Windows Infrastructure

6. Chapter 4: Endpoint Forensic Evidence Collection

7. Part 3: Incident Analysis and Threat Hunting on Windows Systems

8. Chapter 5: Gaining Access to the Network

9. Chapter 6: Establishing a Foothold

10. Chapter 7: Network and Key Assets Discovery

11. Chapter 8: Network Propagation

12. Chapter 9: Data Collection and Exfiltration

13. Chapter 10: Impact

14. Chapter 11: Threat Hunting and Analysis of TTPs

15. Part 4: Incident Investigation Management and Reporting

16. Chapter 12: Incident Containment, Eradication, and Recovery

17. Chapter 13: Incident Investigation Closure and Reporting

18. Index

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19. Other Books You May Enjoy

Anomaly detection – spotting intrusions in Windows environments

Let’s proceed with the hypothesis we made in Figure 11.5. Let’s say that the infrastructure counts more than 30,000 endpoints and the search was run for the past 7 days. The analyst received a shocking 20 million results. What should their approach be to find any threats?

Well, there are four threat-hunting techniques as defined by ACE Responder that could be applied:

Aggregation or stacking: https://x.com/ACEResponder/status/1674564539776368643. This involves counting distinct values for one or more fields and analyzing the bounds for outliers.
Clustering: https://x.com/ACEResponder/status/1675984303568695296. This is the grouping of data based on similar features when the number and nature of different groups may not be fully understood. The analysis can be performed using algorithms suggested (i.e., K-Means, DBSCAN, GMM, K-Modes)..
Searching: https://x.com/ACEResponder/status...

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Authors (2)

Tykushin

Tykushin

Anatoly Tykushin is a services director at Group-IB with 6 years of experience in digital forensics, incident response, compromise assessment, and threat hunting. He has created several DFIR training programs in incident response and network forensics, written several blog posts, and contributed to threat research reports. Outside of DFIR, he has a background in IT administration and DevOps, microcontroller unit development in C, and ASM.

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Ostrovskaya

Ostrovskaya

Svetlana Ostrovskaya is a practicing specialist in digital forensics and incident response at Group-IB. She is the author of DFIR training programs and cybersecurity crisis management workshops, and the author and co-author of blog posts, articles, and books on information security, computer forensics, and incident response.

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