为自然搜索排名提供站点审计、内容撰写与竞品分析。
设计与多媒体
security-threat-model
试用为代码仓库生成结构化的 Markdown 威胁模型,列出信任边界、资产、攻击路径和缓解措施。
它能做什么
接收代码库或指定路径作为输入,输出基于实际仓库结构的应用安全级威胁模型。流程包括提取组件和入口点、识别信任边界与高价值资产、枚举与真实攻击目标对应的滥用路径,并附带明确的概率和影响推理进行优先级排序。最终生成一份简洁的 Markdown 报告。
什么时候用它
- 重大发布或架构变更前的安全评估
- 安全评审或渗透测试的范围界定
- 满足合规要求( SOC2、ISO 27001等)
- 新成员快速了解系统攻击面
技能文档
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
-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.
常见问题
- 支持分析闭源或私有代码吗?
- 只要能访问仓库结构即可工作。分析深度取决于仓库中的文件和架构文档完整程度。
- 如何对威胁进行优先级排序?
- 采用定性概率和影响等级(低/中/高),并附带理由。威胁排序基于概率×影响,并参考现有控制措施进行调整。
- 输出结果是什么格式?
- 一个以仓库名或路径命名的 Markdown 文件,包含组件、信任边界、资产、分类后的滥用路径,以及针对具体位置的高优先级缓解建议。
相关技能
以 AI 机器人身份加入视频会议,提供语音、虚拟形象与屏幕共享四种模式。
docx
官方通过代码创建、编辑和读取 Word .docx 和 .dotx 文件。
读取、合并、拆分、旋转、加水印、创建、加密 PDF,提取文本、表格和图片。
从官方文档出发,基于已有示例代码生成 ChatGPT Apps 项目脚手架。
用团队设计系统的组件和 token 构建或更新 Figma 页面
OpenAI 的更多技能
浏览全部技能从官方文档出发,基于已有示例代码生成 ChatGPT Apps 项目脚手架。
用团队设计系统的组件和 token 构建或更新 Figma 页面
从代码库生成完整的 Figma 设计系统,包含令牌、组件库和主题切换。
通过 Figma Plugin API 在 Figma 文件中执行 JavaScript,符合正确语法和 API 规范。
将品牌线索或参考图转换为支持 Codex 的动画宠物图集,含 QA 交付包。
imagegen
官方通过提示词直接生成或编辑位图图像(照片、插画、纹理、Mockup),内置工具模式无需 API 密钥。