AI supply chain Architecture and Guardrails
RCCE students will learn software and hardware supply chain security including vendor risk assessment, third-party code analysis, dependency management, build pipeline integrity, and supply chain attack detection. RCCE students will learn to evaluate supply chain risks across software development lifecycles, implement software bill of materials (SBOM) practices, verify code signing and artifact integrity, detect compromised dependencies and malicious packages, configure dependency scanning in CI/CD pipelines, assess vendor security posture, and respond to supply chain compromise incidents such as dependency confusion, typosquatting, and upstream repository attacks. This architecture course teaches secure system design using proven patterns, guardrails, and reference architectures. At an expert level, RCCE students will learn to evaluate design options against security requirements, make informed trade-off decisions, and build systems that are resilient by design. Students gain the architectural thinking skills needed for security engineering and solution design roles.
- Security Engineers building defensive controls
- Security Analysts and Blue Team members
- Systems Administrators with security responsibilities
- GRC and Risk Professionals supporting controls
- Professionals implementing AI supply chain Architecture and Guardrails
- Design a scalable privilege management architecture with policy and enforcement
- Execute hands-on tasks for knowledge goals
- Design a scalable privilege management architecture with policy and enforcement, including Skill Outcomes.
- Explain Supply Chain Attack Surface Overview fundamentals
- Execute hands-on tasks for key insight — covering Over 60% of modern codebases consist of open-source dependencies.
- Execute hands-on tasks for what is an sbom? — covering Formal inventory of software components.
- Execute hands-on tasks for required by eo 14028 for federal software — covering SBOM Standards, SPDX (ISO/IEC 5962:2021).
- Execute hands-on tasks for sbom standards — covering SPDX (ISO/IEC 5962:2021).
- Execute hands-on tasks for generation methods — covering Build-time: compiler/linker integration.
- Execute hands-on tasks for consumer use cases — covering Vulnerability tracking across stack.
- Execute hands-on tasks for dependency management and package security
- Execute hands-on tasks for common weaknesses — covering npm (JavaScript) — 2M+ packages.
| Module 01 | AI Supply Chain Architecture |
| Module 02 | Knowledge Goals |
| Module 03 | Architecture Focus |
| Module 04 | Supply Chain Attack Surface Overview |
| Module 05 | Key Insight |
| Module 06 | What Is an SBOM? |
| Module 07 | Required by EO 14028 for federal software |
| Module 08 | SBOM Standards |
| Module 09 | Generation Methods |
| Module 10 | Consumer Use Cases |
| Module 11 | Dependency Management and Package Security |
| Module 12 | Common Weaknesses |
| Module 13 | Dependency Scanning in CI/CD Pipelines |
| Module 14 | License Check |
All hands-on labs run on Rocheston Rose X OS. Students practice ai supply chain architecture and guardrails by implementing the controls discussed in class, with a focus on real-world deployment, monitoring, and validation.
- Lab 1: Design a scalable privilege management architecture with policy and enforcement
- Lab 2: Execute hands-on tasks for knowledge goals
- Lab 3: Design a scalable privilege management architecture with policy and enforcement
- Lab 4: Explain Supply Chain Attack Surface Overview fundamentals
- Lab 5: Execute hands-on tasks for key insight
Upon successful completion of this course, students will receive an official RCCE Course Completion Certificate for AI supply chain Architecture and Guardrails, verifiable through the Rocheston certification portal.
- 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