Security Threat Model

Threat Model Source Code Repo

Overview

This public intake copy packages packages/skills-catalog/skills/(security)/security-threat-model from https://github.com/tech-leads-club/agent-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Threat Model Source Code Repo Deliver an actionable AppSec-grade threat model that is specific to the repository or a project path, not a generic checklist. Anchor every architectural claim to evidence in the repo and keep assumptions explicit. Prioritizing realistic attacker goals and concrete impacts over generic checklists.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Risk prioritization guidance (illustrative, not exhaustive).

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Use when the request clearly matches the imported source intent: Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Use when the user asks to threat model a....
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
• Use when provenance needs to stay visible in the answer, PR, or review packet.
• Use when copied upstream references, examples, or scripts materially improve the answer.
• Use when the workflow should remain reviewable in the public intake repo before the private enhancer takes over.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Identify primary components, data stores, and external integrations from the repo summary.
2. Identify how the system runs (server, CLI, library, worker) and its entrypoints.
3. Separate runtime behavior from CI/build/dev tooling and from tests/examples.
4. Map the in-scope locations to those components and exclude out-of-scope items explicitly.
5. Do not claim components, flows, or controls without evidence.
6. Enumerate trust boundaries as concrete edges between components, noting protocol, auth, encryption, validation, and rate limiting.
7. List assets that drive risk (data, credentials, models, config, compute resources, audit logs).

Imported Workflow Notes

Imported: Workflow

1) Scope and extract the system model

• Identify primary components, data stores, and external integrations from the repo summary.
• Identify how the system runs (server, CLI, library, worker) and its entrypoints.
• Separate runtime behavior from CI/build/dev tooling and from tests/examples.
• Map the in-scope locations to those components and exclude out-of-scope items explicitly.
• Do not claim components, flows, or controls without evidence.

2) Derive boundaries, assets, and entry points

• Enumerate trust boundaries as concrete edges between components, noting protocol, auth, encryption, validation, and rate limiting.
• List assets that drive risk (data, credentials, models, config, compute resources, audit logs).
• Identify entry points (endpoints, upload surfaces, parsers/decoders, job triggers, admin tooling, logging/error sinks).

3) Calibrate assets and attacker capabilities

• List the assets that drive risk (credentials, PII, integrity-critical state, availability-critical components, build artifacts).
• Describe realistic attacker capabilities based on exposure and intended usage.
• Explicitly note non-capabilities to avoid inflated severity.

4) Enumerate threats as abuse paths

• Prefer attacker goals that map to assets and boundaries (exfiltration, privilege escalation, integrity compromise, denial of service).
• Classify each threat and tie it to impacted assets.
• Keep the number of threats small but high quality.

5) Prioritize with explicit likelihood and impact reasoning

• Use qualitative likelihood and impact (low/medium/high) with short justifications.
• Set overall priority (critical/high/medium/low) using likelihood x impact, adjusted for existing controls.
• State which assumptions most influence the ranking.

6) Validate service context and assumptions with the user

• Summarize key assumptions that materially affect threat ranking or scope, then ask the user to confirm or correct them.
• Ask 1–3 targeted questions to resolve missing context (service owner and environment, scale/users, deployment model, authn/authz, internet exposure, data sensitivity, multi-tenancy).
• Pause and wait for user feedback before producing the final report.
• If the user declines or can’t answer, state which assumptions remain and how they influence priority.

7) Recommend mitigations and focus paths

• Distinguish existing mitigations (with evidence) from recommended mitigations.
• Tie mitigations to concrete locations (component, boundary, or entry point) and control types (authZ checks, input validation, schema enforcement, sandboxing, rate limits, secrets isolation, audit logging).
• Prefer specific implementation hints over generic advice (e.g., "enforce schema at gateway for upload payloads" vs "validate inputs").
• Base recommendations on validated user context; if assumptions remain unresolved, mark recommendations as conditional.

8) Run a quality check before finalizing

• Confirm all discovered entrypoints are covered.
• Confirm each trust boundary is represented in threats.
• Confirm runtime vs CI/dev separation.
• Confirm user clarifications (or explicit non-responses) are reflected.
• Confirm assumptions and open questions are explicit.
• Confirm that the format of the report matches closely the required output format defined in prompt template: references/prompt-template.md
• Write the final Markdown to a file named <repo-or-dir-name>-threat-model.md (use the basename of the repo root, or the in-scope directory if you were asked to model a subpath).

Imported: Risk prioritization guidance (illustrative, not exhaustive)

• High: pre-auth RCE, auth bypass, cross-tenant access, sensitive data exfiltration, key or token theft, model or config integrity compromise, sandbox escape.
• Medium: targeted DoS of critical components, partial data exposure, rate-limit bypass with measurable impact, log/metrics poisoning that affects detection.
• Low: low-sensitivity info leaks, noisy DoS with easy mitigation, issues requiring unlikely preconditions.

Examples

Example 1: Ask for the upstream workflow directly

Use @security-threat-model to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @security-threat-model against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @security-threat-model for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @security-threat-model using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Quick start

1. Collect (or infer) inputs:

• Repo root path and any in-scope paths.
• Intended usage, deployment model, internet exposure, and auth expectations (if known).
• Any existing repository summary or architecture spec.
• Use prompts in references/prompt-template.md to generate a repository summary.
• Follow the required output contract in references/prompt-template.md. Use it verbatim when possible.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in packages/skills-catalog/skills/(security)/security-threat-model, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @accessibility - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ai-cold-outreach - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ai-pricing - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ai-sdr - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

• prompt-template.md
• security-controls-and-assets.md
• LICENSE.txt
• prompt-template.md
• security-controls-and-assets.md

Imported Reference Notes

Imported: References

• Output contract and full prompt template: references/prompt-template.md
• Optional controls/asset list: references/security-controls-and-assets.md

Only load the reference files you need. Keep the final result concise, grounded, and reviewable.