SKILL

threat-modeling

Works out what could go wrong in a system's design before it is built — who would attack it, how, and which defences are worth having. Use this whenever the user is designing a system that handles sensitive data, money, or authentication, asks what the security risks are, mentions threat modeling or STRIDE, or is starting a feature with a meaningful attack surface. This is design-time and systematic; for finding vulnerabilities in code that exists, use security-analysis.

Target: Design & content creation. Automatically collected · unverified.

Excerpt from the author’s documentation

Extracted from a fixed version of SKILL.md in its original language. This is the author’s documentation; installation, compatibility and runtime results have not been verified by this site.

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Topics in the source

  • Threat modeling
  • 1. Draw the system and mark the trust boundaries
  • 2. Name the attackers and what they want
  • 3. Walk each element with a prompt list
  • 4. Prioritise by reachability and impact
  • 5. Prefer structural mitigations
  • 6. Write it down briefly, and revisit it
  • Report

Threat modeling asks what could go wrong here while the answer is still cheap to act on. Code review finds the bug you wrote; threat modeling finds the defence you never designed. Four questions structure the whole exercise: 1. What are we building? 2. What can go wrong? 3. What are we going to do about it? 4. Did we do a good enough job? The output is a short list of decisions, not a risk register nobody reads. You cannot reason about attacks without knowing where untrusted things meet trusted things. Sketch: the components, the data flows between them, the datastores, and — most importantly — the trust boundaries those flows cross. A boundary is anywhere the level of trust changes: internet to your edge, your service to a third party, one tenant's data to another's, user to admin. Keep it to one diagram someone can hold in their head. See diagramming. Done when: every trust boundary in the design is marked. Generic "hackers" produces generic mitigations. Be specific about who and why: An anonymous internet user: the largest population, lowest capability A legitimate user acting maliciously: has valid credentials. Most under-modelled, and the source of most real access-control fai

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Source repository
OKHP3/skillz
Source file
community/threat-modeling/SKILL.md
Fixed revision
7b187777d42ab7bc7bab1e5f2c940cd3139ecebf
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Author: OKHP3/skillz · original repository metadata. Documentation review: Not reviewed. Last source check: 2026-11-10T10:00:54.396Z.

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