Learn a pattern-oriented approach to using the Microsoft Debugger (WinDbg) in the context of kernel and complete memory spaces and C and C++ memory thinking.

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For the approximate content, please see the slides from the previous training:

This comprehensive Windows and Linux API training pack for software technical support engineers, system administrators, DevOps and DevSecOps, security engineers, vulnerability researchers, malware and memory forensics analysis, software developers, and testers features:

Solid C and C++ knowledge is a must to fully understand Linux and Windows diagnostic artifacts, such as memory dumps, and perform diagnostic, forensic, and root cause analysis beyond listing stack traces. This training pack features:

The training pack contains the full transcripts of the two Software Diagnostics Services training courses. Learn disassembly, execution history reconstruction, and binary reversing techniques for better software diagnostics, troubleshooting, debugging, memory forensics, vulnerability and malware analysis on x64 Windows, x64 and ARM64 Linux platforms. The course uses a unique and innovative pattern language approach to speed up the learning curve. The training consists of practical step-by-step, hands-on exercises using WinDbg, GDB, Windows and Linux memory dumps.

This comprehensive training for software technical support engineers, system administrators, DevOps, software developers and testers, site reliability and performance engineers teaches the analysis of all memory spaces for patterns of abnormal software behavior in process, kernel, and complete (physical) memory dumps and features:

This comprehensive training for software developers, cloud, site reliability, and performance engineers, DevOps, and DevSecOps teaches postmortem, live local and remote debugging techniques and features:

This comprehensive training for software developers, site reliability, and performance engineers teaches postmortem, live local, and remote debugging techniques using the Microsoft WinDbg debugger and features: