openai/skills/skills/.curated/security-threat-model/SKILL.md
security-threat-model
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only when the user explicitly asks to threat model a codebase or path, enumerate threats/abuse paths, or perform AppSec threat modeling. Do not trigger for general architecture summaries, code review, or non-security design work.
- Source repository stars
- 24,265
- Declared platforms
- 0
- Static risk flags
- 1
- Last source update
- 2026-07-14
- Source checked
- 2026-07-28
Decision brief
What it does—and where it fits
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…
Not for
- Tasks that require unconfirmed production actions or broad system permissions.
- Environments where the pinned source and install steps cannot be inspected.
Compatibility matrix
Platform support, with evidence labels
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
Inspect first. Install second.
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/openai/skills --skill "skills/.curated/security-threat-model"Inspect the Agent Skill "security-threat-model" from https://github.com/openai/skills/blob/49f948faa9258a0c61caceaf225e179651397431/skills/.curated/security-threat-model/SKILL.md at commit 49f948faa9258a0c61caceaf225e179651397431. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
What the source asks the agent to do
- 01
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 re…
Collect (or infer) inputs:Repo root path and any in-scope paths.Intended usage, deployment model, internet exposure, and auth expectations (if known). - 02
Workflow
Identify primary components, data stores, and external integrations from the repo summary.
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. - 03
1) Scope and extract the system model
Identify primary components, data stores, and external integrations from the repo summary.
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. - 04
2) Derive boundaries, assets, and entry points
Enumerate trust boundaries as concrete edges between components, noting protocol, auth, encryption, validation, and rate limiting.
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). - 05
3) Calibrate assets and attacker capabilities
List the assets that drive risk (credentials, PII, integrity-critical state, availability-critical components, build artifacts).
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.
Permission review
Static risk signals and limitations
Writes files
The documentation asks the agent to create, modify, or delete local files.
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).Evidence record
Why each signal appears
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 76/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 24,265 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Provenance and original SKILL.md
- Repository
- openai/skills
- Skill path
- skills/.curated/security-threat-model/SKILL.md
- Commit
- 49f948faa9258a0c61caceaf225e179651397431
- License
- Not declared
- Collected
- 2026-07-28
- Default branch
- main
View the original SKILL.md
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.
Quick start
- 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.mdto generate a repository summary. - Follow the required output contract in
references/prompt-template.md. Use it verbatim when possible.
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).
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.
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.
Alternatives
Compare before choosing
JasonColapietro/suede-creator-skills
suede-workflow-skills
Umbrella workflow for 67 public skills: Full Send, copy, design, code review, SEO, launch packaging, MCP QA, iOS and Android app shipping, and creator workflows. Loads the full public skill pack.
github/awesome-copilot
copilot-pr-autopilot
Copilot left 14 review comments on your PR — half are nits. Hours of fix → reply → resolve → re-request, and each round lands MORE comments. This skill runs loop engineering: auto-triggers Copilot Code Review via GraphQL (no @copilot mention), triages every open thread (Copilot, humans, advanced-security) with a fix / decline / escalate rubric, dispatches parallel fix sub-agents that obey the repo build/test/lint conventions, commits per iteration, replies+resolves citing the pushed SHA, then re
JasonColapietro/suede-creator-skills
suede-code-review
Find the bugs a diff can actually ship: TypeScript, React, Next.js, OWASP, accessibility, SEO, database, and deploy-risk review. Return findings, not a grade.
github/awesome-copilot
postgresql-code-review
PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).