Zero Trust is not a product but an architecture philosophy: "Never trust, always verify." This lab guides you through implementing Zero Trust across all five pillars—Identity, Devices, Networks, Applications, and Data—using the technologies from previous labs. You'll learn to design, implement, and validate a comprehensive Zero Trust architecture for enterprise environments.
Zero Trust assumes breach and verifies every request as if it originated from an untrusted network. The goal is to minimize the blast radius of any compromise by eliminating implicit trust.
Strong authentication, MFA, least privilege, JIT access
Device health, compliance, endpoint security
Micro-segmentation, encrypted traffic, ZTNA
App-level auth, secure APIs, shadow IT control
Classification, encryption, DLP, access controls
Evaluates requests against policy | Entra ID CA, AWS IAM, GCP IAM
Enforces access decisions | Proxy, Gateway, API Gateway
Provides context | Device compliance, Risk score, User attributes
Manages policies | Admin console, IaC, Policy repository
| Traditional (Perimeter) | Zero Trust |
|---|---|
| Trust users inside network | Trust no one by default |
| One-time authentication | Continuous verification |
| Network-based access | Identity-based access |
| Flat internal network | Micro-segmented network |
| VPN for remote access | ZTNA per-app access |
| Implicit trust after auth | Least privilege always |
Identity is the foundation of Zero Trust—verify every user, every time.
Verify device health and compliance before granting access.
Move from network perimeter to micro-segmented, identity-aware access.
Move authentication and authorization to the application layer.
Classify, encrypt, and control access to sensitive data.
Implement continuous authentication and risk assessment.
Extend Zero Trust principles to cloud infrastructure and SaaS applications.
Assess current state and build implementation roadmap.
Perimeter-based security, VPN access, passwords only, flat network, implicit trust inside
MFA deployed, some SSO, basic network segmentation, endpoint protection
Risk-based auth, device compliance, micro-segmentation, CASB, some automation
Continuous verification, full ZTNA, automated response, data-centric security
ML-driven decisions, real-time risk, self-healing, fully automated, predictive
Strong authentication, MFA, identity verification
Managed, compliant, healthy, encrypted
Location, time, behavior, threat signals
Sensitivity level, data classification
Least privilege, need to know, JIT
Session controls, CAE, anomaly detection