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About the Book
The full transcript of Software Diagnostics Services training. Learn how to navigate process, kernel, and physical spaces and diagnose various malware patterns in Windows memory dump files. The course uses a unique and innovative pattern-oriented analysis approach to speed up the learning curve. The training consists of practical step-by-step, hands-on exercises using WinDbg, process, kernel, and complete memory dumps. The training covers more than 20 malware analysis patterns. The main audience is software technical support and escalation engineers who analyze memory dumps from complex software environments and need to check for possible malware presence in cases of abnormal software behavior. The course will also be useful for software engineers, quality assurance and software maintenance engineers, security researchers, malware and memory forensics analysts who have never used WinDbg for analysis of computer memory. The third edition uses the latest WinDbg Preview version with some exercises updated to Windows 11 and is optionally containerized.
About the Author
Dmitry Vostokov is an internationally recognized expert, speaker, educator, scientist, inventor, and author. He founded the pattern-oriented software diagnostics, forensics, and prognostics discipline (Systematic Software Diagnostics) and Software Diagnostics Institute. Vostokov has also authored over 50 books on software diagnostics, anomaly detection and analysis, software and memory forensics, root cause analysis and problem solving, memory dump analysis, debugging, software trace and log analysis, reverse engineering, and malware analysis. He has over 30 years of experience in software architecture, design, development, and maintenance in various industries, including leadership, technical, and people management roles. Dmitry founded OpenTask Iterative and Incremental Publishing and Software Diagnostics Technology and Services (former Memory Dump Analysis Services). In his spare time, he explores Software Narratology and Quantum Software Diagnostics. His interest areas are theoretical software diagnostics and its mathematical and computer science foundations, application of formal logic, semiotics, artificial intelligence, machine learning, and data mining to diagnostics and anomaly detection, software diagnostics engineering and diagnostics-driven development, diagnostics workflow and interaction. Recent interest areas also include functional programming, cloud native computing, monitoring, observability, visualization, security, automation, applications of category theory to software diagnostics, development and big data, and diagnostics of artificial intelligence.