SecureTheCloud Labs — AI Track Sequence

Status: AI Track Sequence Baseline

Purpose

Define the intended sequence for SecureTheCloud AI learning tracks.

Track 1 — AI Governance Command Center

Status:

Completed / Quality Gated

Purpose:

Teach AI governance, risk tiering, policy gates, approvals, evidence, and operational boundaries.

Best for:

Executives
Governance teams
GRC teams
Risk owners
Platform leads
Security architects
AI program managers
Track 2 — AI Security Engineering

Status:

Planned

Purpose:

Teach how to engineer secure AI systems using prompt boundaries, tool permissions, retrieval controls, runtime guardrails, test harnesses, and evidence packages.

Best for:

Security engineers
Cloud engineers
Platform engineers
AI application builders
DevSecOps teams
Detection engineers
Security architects
Track 3 — AI Red Team Scenario Design

Status:

Future

Purpose:

Teach adversarial AI testing, prompt injection scenarios, retrieval poisoning tests, tool-hijack simulation, abuse-case modeling, and defensive validation.

Best for:

Red teams
AppSec teams
AI security testers
Threat modelers
Security researchers
Detection teams
Recommended Learner Route
AI Governance Command Center
→ AI Security Engineering
→ AI Red Team Scenario Design
Boundary

This is a curriculum sequence document only.

It does not create a new deployed system, expose a backend, mutate runtime infrastructure, or claim production enforcement.