RCCE Course
Course #1043

TPM, HSM, and Hardware Root of Trust

📊 Level: Intermediate
⏱️ Duration: 2 Days
🏷️ Track: Cryptography & PKI
📋 Prerequisites: Foundations
🖥️ Mode: Online Instructor-Led
📝 Course Description

RCCE students will learn how trusted platform modules, hardware security modules, secure elements, and hardware roots of trust strengthen identity, encryption, attestation, and key protection. RCCE students will learn to design secure key custody models, evaluate attestation workflows, protect secrets from extraction, understand measured boot concepts, and integrate hardware-backed trust into enterprise and cloud architectures. The course covers practical scenarios ranging from device attestation to protected cryptographic operations and key lifecycle management. RCCE students will learn to analyze complex systems and think like an attacker to better defend the organization. This comprehensive course delivers practical knowledge applicable to real-world cybersecurity operations. Starting from foundational concepts, RCCE students will learn through a combination of concept explanation, practical demonstration, and hands-on exercises.

🎯 Target Audience
  • Security Engineers building defensive controls
  • Security Analysts and Blue Team members
  • Systems Administrators with security responsibilities
  • GRC and Risk Professionals supporting controls
  • Professionals implementing TPM, HSM, and Hardware Root of Trust
🧠 What You Will Learn
  • Integrate privilege controls with identity providers and SIEM telemetry
  • Explain Course Overview fundamentals
  • Execute hands-on tasks for scope & depth
  • Execute hands-on tasks for hands-on focus
  • Integrate privilege controls with identity providers and SIEM telemetry, including Key generation ceremonies.
  • Execute hands-on tasks for topic map — 18 learning domains
  • Execute hands-on tasks for principle: trust must start in hardware
  • Execute hands-on tasks for key properties: — covering Immutability — cannot be modified by software.
  • Explain TPM Architecture Overview fundamentals
  • Execute hands-on tasks for crypto engine
  • Execute hands-on tasks for key hierarchy
  • Execute hands-on tasks for random generator
📚 Course Outline
Module 01Strengthening Identity, Encryption, Attestation & Key Protection
Module 02Course Overview
Module 03Scope & Depth
Module 04Hands-On Focus
Module 05Cloud HSM integration patterns
Module 06Topic Map — 18 Learning Domains
Module 07Principle: Trust must start in hardware
Module 08Key Properties:
Module 09TPM Architecture Overview
Module 10Crypto Engine
Module 11Key Hierarchy
Module 12Random Generator
Module 13HSM Architecture & Deployment Models
Module 14Hardware Security Module:
🧪 Lab Details

All hands-on labs run on Rocheston Rose X OS. Students practice tpm, hsm, and hardware root of trust by implementing the controls discussed in class, with a focus on real-world deployment, monitoring, and validation.

  • Lab 1: Integrate privilege controls with identity providers and SIEM telemetry
  • Lab 2: Explain Course Overview fundamentals
  • Lab 3: Execute hands-on tasks for scope & depth
  • Lab 4: Execute hands-on tasks for hands-on focus
  • Lab 5: Integrate privilege controls with identity providers and SIEM telemetry
📊 Skill Level
Intermediate
Beginner Intermediate Advanced Expert
Duration
2 Days
🎓
Certificate
Completion
🖥️
Lab Platform
Rose X OS
👨‍🏫
Mode of Training
Online Instructor-Led
🔥
Platform
Zelfire
🐦‍⬛
Cyber Range
Raven
📓
Study Material
CyberNotes
🏆 Certificate

Upon successful completion of this course, students will receive an official RCCE Course Completion Certificate for TPM, HSM, and Hardware Root of Trust, verifiable through the Rocheston certification portal.

🔑 Student Access & Materials
  • Full access to all course materials and slide decks
  • Hands-on lab access on Rocheston Rose X OS environment
  • Access to Rocheston CyberNotes
  • Access to Rocheston Zelfire — EDR/XDR SIEM platform
  • Access to Rocheston Raven — online cyber range exercise platform
  • Access to Rocheston Vulnerability Vines AI