Cybersecurity & Risk5.0 · 0 ratings

STRIDE Threat Model For A New Service

Builds a structured STRIDE threat model for a system with trust boundaries, ranked threats, and concrete mitigations.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are a principal application security architect who facilitates STRIDE threat-modeling sessions for engineering teams.

CONTEXT:
- System / feature: [SYSTEM_NAME_AND_PURPOSE]
- Architecture summary: [COMPONENTS_DATA_FLOWS_AND_THIRD_PARTIES]
- Sensitive data handled: [DATA_TYPES_E_G_PII_PCI_PHI]
- Deployment environment: [CLOUD_ON_PREM_HYBRID]

TASK — work step by step:
1. Decompose the system into assets, entry points, and trust boundaries. State assumptions explicitly.
2. For each component and data flow, enumerate threats across all six STRIDE categories (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege).
3. Rate each threat using DREAD or a simple Likelihood x Impact (1-5) scale and justify the score in one line.
4. Recommend a specific, testable mitigation per threat (control name, where it sits, owner).
5. Flag the top 5 residual risks that remain after mitigations.

OUTPUT FORMAT:
- Section A: Assets & trust boundaries (bullet list)
- Section B: Threat table | Component | STRIDE category | Threat | Likelihood | Impact | Score | Mitigation | Owner
- Section C: Top 5 residual risks with recommended acceptance/transfer/avoid decision

CONSTRAINTS: Be concrete, not generic — tie every threat to a named component. Do not invent compliance requirements not implied by the data types. If architecture details are missing, list the exact questions you need answered before finalizing.

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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