stride-analysis-patterns – Data & Science skill for AI agents

STRIDE Analysis Patterns

Systematic threat identification using the STRIDE methodology.

Use this skill when

• Starting new threat modeling sessions
• Analyzing existing system architecture
• Reviewing security design decisions
• Creating threat documentation
• Training teams on threat identification
• Compliance and audit preparation

Do not use this skill when

• The task is unrelated to stride analysis patterns
• You need a different domain or tool outside this scope

Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open resources/implementation-playbook.md.

Resources

• resources/implementation-playbook.md for detailed patterns and examples.

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Modeling and scoring limits

The Python helpers produce prompts from user-supplied model data; they do not inspect software or establish actual vulnerabilities, control effectiveness or compliance. Impact×likelihood and all severities/deadlines in examples are illustrative ordinal policy choices, not CVSS or calibrated probabilities. Record evidence, assumptions, assets, trust boundaries, owners and residual-risk acceptance for each candidate. Equal numeric trust levels can still cross tenant/identity/administrative boundaries; model explicit boundary membership rather than relying solely on inequality. Encryption does not prevent authorized-but-abusive access, and authentication lockouts can create denial-of-service risks. Missing elements or unmodeled interaction types must be surfaced, not silently treated as no threats. Templates are partial independent blocks; validate imports, duplicate IDs and structured model inputs before use. Keep secret-bearing diagrams/logs private and do not run attack simulations without separate authorization.