Use this skill when you need evidence-bounded threat-modeling analysis and validation preparation; triggers include 威胁建模 and threat-modeling.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Threat Modeling
## When to Use
- Use this Skill when the work needs evidence-bounded analysis of assets, trust boundaries, attack surface, threat scenarios, mitigations, and assumptions.
- Use it when input is incomplete but a reviewable draft with assumptions and gaps is still useful.
- Use it when static security evidence must remain separate from planned validation and completed execution.
## Output Format Options
- Default to Markdown organized by security risk, evidence, and priority.
- If the user asks for a table, CSV, JSON, or ticket format, preserve the same finding fields and evidence states.
- Confirm the schema, enum values, and required fields before feeding the output to automation.
## How to Use
1. Read prompts/threat-modeling.md and follow its input audit, coverage checklist, and output contract.
2. Extract scope, environment, version, roles, data, dependencies, constraints, and available evidence.
3. Model assets, trust boundaries, attack surface, threat scenarios, mitigations, and assumptions with reviewable scenarios, separating known facts, inferences, and candidate validation.
…
The line at the top of this page pins the label git:20260915.543141a, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
pass: Frontmatter block present
pass: Frontmatter declares a name
pass: Frontmatter declares a description
pass: Size between 200 bytes and 200 KB (3313 bytes)
pass: No zero-width or bidi control characters
pass: No instruction hidden inside an HTML comment
pass: No link to an exfiltration or paste host
pass: No credential-shaped string
pass: No instruction to send local credentials anywhere
pass: No text hidden with inline styles
pass: No prompt-injection phrasing
pass: No curl or wget piped into a shell
pass: No recursive delete of root, home or parent
pass: No instruction to read or print local credentials
pass: No base64 blob over 200 characters
pass: No link to a raw IP address
pass: No script tag
Source
GitHub
naodeng/awesome-qa-skills · 279 stars · license a license file GitHub does not identify · pushed 2026-10-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_4x43ao2wsj66otmt
GET https://markdownregistry.com/api/v1/resolve?ref=naodeng/awesome-qa-skills/threat-modeling
GET https://markdownregistry.com/api/v1/blob/5fa5f845bcd3fe622e1af0d4bf2adfc0c3d1e9ede8966d287c3b5e5205963b72
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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