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Threat Modeling (STRIDE) Assistant

Run a full STRIDE threat model: numbered threats, risk scores, mitigations, trust boundaries, and compliance control mapping for any architecture.

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Edit the values, then copy your finished prompt.

Jouw Prompt
prompt.txt

                                

What this prompt does

This prompt runs a systematic STRIDE analysis across every component you describe in [architecture_description], producing numbered threat IDs, likelihood x impact risk scores, and prioritised mitigations in a single pass. The structure forces the model to touch all six STRIDE categories per component rather than stopping at the obvious spoofing and injection vectors most ad-hoc security reviews miss — repudiation and elevation of privilege are the two categories engineers chronically skip, and the template explicitly calls them out.

The [data_classification] and [compliance] variables do real work here. Feeding in "PII + PCI-DSS" versus "internal metrics + no regulatory requirement" changes which threats get elevated risk scores and which mitigations the model prioritises. The final compliance control mapping section ties every critical finding back to the specific standard you named, giving you an artefact you can drop directly into an audit package.

When to use it

  • Designing a new API gateway or microservice boundary before writing a line of code
  • Pre-launch security review for a SaaS product handling financial or health data
  • Preparing evidence for ISO 27001, SOC 2, or PCI-DSS auditors who require documented threat modelling
  • Onboarding a new team member who needs to understand the attack surface of an inherited system
  • Responding to a security incident by re-modelling the affected component to find adjacent risks
  • Architecture review sessions where you want a structured threat register as a discussion anchor

Example output

Threat ID: T-007
STRIDE Category: Elevation of Privilege
Component: Internal Admin API (/api/v1/admin)
Attack Vector:
  1. Attacker obtains a valid user JWT via phishing
  2. Sends forged request with manually crafted role claim ("role": "admin")
  3. API trusts the claim without server-side role lookup
  4. Full admin access granted

Impact: Confidentiality (HIGH), Integrity (HIGH), Availability (LOW)
Likelihood: 4 | Impact: 5 | Risk Score: 20 (CRITICAL)

Mitigation: Validate role claims server-side against the users table on every
request; never trust JWT payload for authorisation decisions. Priority: P0.
Residual Risk: Low (score ~4) after server-side role enforcement.

Pro tips

  • Fill [architecture_description] in DFD terms. List components as nodes ("React SPA → API Gateway → Auth Service → PostgreSQL") with data flows between them. Vague prose produces vague threats.
  • Set [top_count] to 5 for boards, 10 for engineering teams. The summary section is the artefact executives actually read; calibrate it to your audience.
  • Use real compliance shorthand. "PCI-DSS v4.0 Req 6.4" gets you more precise control mapping than "PCI-DSS". The model knows the standard numbers.
  • Run it twice for large systems — once per trust boundary (e.g., public-facing tier, internal service mesh). A single monolithic pass over a 10-component architecture dilutes the threat density per component.
  • Pair with a follow-up prompt asking for abuse cases. STRIDE covers structural threats; adversarial abuse cases (account takeover flows, scraping attacks) live in the business logic layer and need a separate sweep.

Frequently Asked Questions

Does this prompt work for cloud architectures (AWS, GCP, Azure) or only on-premise systems?
It works for any architecture you can describe in text. For cloud systems, be explicit in [architecture_description] — name the services (e.g., "API Gateway → Lambda → RDS in a private VPC"). The more specific your component list, the more precise the threat IDs. Shared-responsibility boundaries like managed TLS or cloud IAM are worth noting in [existing_controls] so the model does not flag mitigations you already get from the provider.
How accurate are the risk scores the model produces?
The 1–5 likelihood and impact scores are calibrated estimates based on the context you supply — they are a structured thinking aid, not a validated CVSS equivalent. Treat them as a prioritisation signal to drive your engineering conversation, not as audit-grade measurements. If you need defensible numbers for a compliance artefact, use the model output as a first draft and have a security engineer validate the scores against your actual environment.
Can I use this for a system I cannot fully describe (e.g., a black-box third-party integration)?
Yes, but scope it honestly. Describe what you know — the integration's exposed interface, the data it receives, and the trust level you assign it — and flag the gaps explicitly in [architecture_description]. The model will surface threats based on what it can infer about the interface boundary, and the residual risk ratings will reflect the uncertainty. Partial threat models are still far more useful than none.
Engr Mejba Ahmed

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Engr Mejba Ahmed

AI Developer · Software Engineer

I'm Mejba — I design and ship production AI systems, automations, and full-stack apps. If you want this turned into a working solution for your team, let's talk.

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Engr Mejba Ahmed

Engr Mejba Ahmed

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