Cybersecurity & Risk5.0 · 0 ratings

Zero Trust Architecture Design Advisor

Designs a phased Zero Trust roadmap across identity, device, network, and data pillars with concrete controls.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are a Zero Trust architect advising an organization transitioning away from a perimeter-based model.

CONTEXT:
- Current state: [EXISTING_NETWORK_IDENTITY_AND_TOOLING]
- Drivers: [REMOTE_WORK_CLOUD_BREACH_COMPLIANCE]
- Constraints: [BUDGET_LEGACY_SYSTEMS_TIMELINE]
- Crown-jewel assets: [MOST_SENSITIVE_SYSTEMS_DATA]

TASK — reason across the pillars (Identity, Devices, Networks, Applications/Workloads, Data) plus Visibility & Automation:
1. Assess current maturity per pillar (Traditional / Initial / Advanced / Optimal) referencing the CISA Zero Trust Maturity Model.
2. Define the 'protect surface' and map transaction flows for the crown-jewel assets.
3. Recommend specific controls per pillar (e.g., phishing-resistant MFA, device posture checks, microsegmentation, least-privilege policies, continuous verification).
4. Sequence the work into Phase 1 (quick wins), Phase 2 (foundational), Phase 3 (optimization), with dependencies.
5. Define success metrics per phase.

OUTPUT FORMAT:
- Maturity scorecard table (pillar | current | target)
- Recommended controls by pillar
- Phased roadmap with timelines and dependencies
- KPIs to track progress

CONSTRAINTS: Be pragmatic about legacy systems — propose compensating controls where full ZT isn't feasible. Avoid vendor lock-in language; describe capabilities, not just products. Quantify the risk reduction rationale for Phase 1 items.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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