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Agent Skill · 前端设计

threat-model-generation(威胁模型生成)

threat-model-generation 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

threat-model-generation 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 4,288。

总安装 930周安装 38GitHub Stars 64下载 301核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:threat-model-generation(威胁模型生成)
来源仓库:https://github.com/factory-ai/factory-plugins
仓库路径:skills/threat-model-generation
安装命令:
npx skills add https://github.com/factory-ai/factory-plugins --skill threat-model-generation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/factory-ai/factory-plugins --skill threat-model-generation

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

用于处理 GitHub 仓库、Issue、Pull Request 等协作信息。适合围绕代码变更、问题跟踪或团队协作事项进行结构化整理。可生成变更摘要、影响范围图或风险提示,提升项目管理透明度。

安装命令:npx skills add https://github.com/factory-ai/factory-plugins --skill threat-model-generation。需确认是否集成可视化图表生成功能,以便直观展示结果。

来源仓库内路径:skills/threat-model-generation

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/factory-ai/factory-plugins --skill threat-mode…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

threat-model-generation 怎么安装?

在终端执行 npx skills add https://github.com/factory-ai/factory-plugins --skill threat-model-generati…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

threat-model-generation 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

threat-model-generation 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

threat-model-generation 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

threat-model-generation 用的人多吗?

公开数据是累计安装 930 次,近一周安装 38 次,下载 301 次,GitHub 64 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

threat-model-generation 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
threat-model-generation

威胁模型生成 · 本页

93064接触敏感数据未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Threat Model Generation

Generate a comprehensive security threat model for a repository using the STRIDE methodology. This skill analyzes the codebase architecture and produces an LLM-optimized threat model document that other security skills can reference.

When to Use This Skill

  • First-time setup - New repository needs initial threat model
  • Architecture changes - Significant changes to components, APIs, or data flows
  • Security audit - Periodic review or compliance requirement
  • Manual request - Security team requests updated threat model

Inputs

Before running this skill, gather or confirm:

InputDescriptionRequired
Repository pathRoot directory to analyzeYes (default: current directory)
Existing threat modelPath to existing .factory/threat-model.md if updatingNo
Compliance requirementsFrameworks to consider (SOC2, GDPR, HIPAA, etc.)No
Security contactsEmail addresses for security team notificationsNo

Instructions

Follow these steps in order:

Step 1: Analyze Repository Structure

Scan the codebase to understand the system:

  1. Identify languages and frameworks

- Check package.json, requirements.txt, go.mod, Cargo.toml, etc. - Note the primary tech stack (e.g., Next.js, Django, Go microservices)

  1. Map components and services

- Look for apps/, services/, packages/ directories - Identify entry points: API routes, CLI commands, web handlers - Note databases, caches, message queues

  1. Identify external interfaces

- HTTP endpoints (REST, GraphQL) - File upload handlers - Webhook receivers - OAuth/SSO integrations - CLI commands that accept user input

  1. Trace data flows

- How does user input enter the system? - Where is sensitive data stored? - What external services are called?

Step 2: Identify Trust Boundaries

Define security zones:

  1. Public Zone (untrusted)

- All external HTTP endpoints - Public APIs without authentication - User-uploaded files

  1. Authenticated Zone (partially trusted)

- Endpoints requiring valid session/token - User-specific data access - Rate-limited APIs

  1. Internal Zone (trusted)

- Service-to-service communication - Admin-only endpoints - Database connections - Secrets management

Document where trust boundaries exist and what validates transitions between zones.

Step 3: Inventory Critical Assets

Classify data by sensitivity:

  1. PII (Personally Identifiable Information)

- User emails, names, addresses, phone numbers - Document protection measures

  1. Credentials & Secrets

- Password hashes, API keys, OAuth tokens - JWT signing keys, encryption keys - Document rotation policies

  1. Business-Critical Data

- Transaction records, customer data - Proprietary algorithms, trade secrets - Document access controls

Step 4: Apply STRIDE Analysis

For each major component, analyze threats in all six categories:

S - Spoofing Identity
  • Can attackers impersonate users or services?
  • Are authentication mechanisms secure?
  • Look for: weak session handling, API key exposure, missing MFA
T - Tampering with Data
  • Can attackers modify data in transit or at rest?
  • Look for: SQL injection, XSS, mass assignment, missing input validation
R - Repudiation
  • Can users deny actions they performed?
  • Look for: missing audit logs, insufficient logging, no immutable trails
I - Information Disclosure
  • Can attackers access data they shouldn't?
  • Look for: IDOR, verbose errors, hardcoded secrets, data leaks in logs
D - Denial of Service
  • Can attackers disrupt service availability?
  • Look for: missing rate limits, resource exhaustion, algorithmic complexity
E - Elevation of Privilege
  • Can attackers gain unauthorized access levels?
  • Look for: missing authorization checks, role manipulation, privilege escalation

For each identified threat:

  • Describe the attack scenario
  • List vulnerable components
  • Show code patterns to look for
  • Note existing mitigations
  • Identify gaps
  • Assign severity (CRITICAL/HIGH/MEDIUM/LOW) and likelihood

Step 5: Document Vulnerability Patterns

Create a library of code patterns specific to this codebase's tech stack:

# Example: SQL Injection patterns for Python
# VULNERABLE
sql = f"SELECT * FROM users WHERE id = {user_id}"

# SAFE
cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))

Include patterns for:

  • SQL injection
  • XSS (Cross-Site Scripting)
  • Command injection
  • Path traversal
  • Authentication bypass
  • IDOR (Insecure Direct Object Reference)

Step 6: Generate Output Files

Create two files:

1. .factory/threat-model.md

Use the template in stride-template.md to generate a comprehensive threat model with:

  • System overview with architecture description
  • Trust boundaries and security zones
  • Attack surface inventory
  • Critical assets classification
  • STRIDE threat analysis for each component
  • Vulnerability pattern library
  • Security testing strategy
  • Assumptions and accepted risks
  • Version changelog

The document should be written in natural language with code examples, optimized for LLM comprehension.

2. .factory/security-config.json

Generate configuration metadata:

{
  "threat_model_version": "1.0.0",
  "last_updated": "<ISO timestamp>",
  "security_team_contacts": [],
  "compliance_requirements": [],
  "scan_frequency": "on_commit",
  "severity_thresholds": {
    "block_merge": ["CRITICAL"],
    "require_review": ["HIGH", "CRITICAL"],
    "notify_security_team": ["CRITICAL"]
  },
  "vulnerability_patterns": {
    "enabled": [
      "sql_injection",
      "xss",
      "command_injection",
      "path_traversal",
      "auth_bypass",
      "idor"
    ],
    "custom_patterns_path": null
  }
}

Customize based on:

  • Detected compliance requirements (from docs, configs, or user input)
  • Security team contacts (if provided)
  • Tech stack (enable relevant vulnerability patterns)

Success Criteria

The skill is complete when:

  • .factory/threat-model.md exists with all sections populated
  • .factory/security-config.json exists with valid JSON
  • All major components have STRIDE analysis
  • Vulnerability patterns match the tech stack
  • Document is written in natural language (LLM-readable)
  • No placeholder text remains

Verification

Run these checks before completing:

# Verify threat model exists and is non-empty
test -s .factory/threat-model.md && echo "✓ Threat model exists"

# Verify config is valid JSON
cat .factory/security-config.json | jq . > /dev/null && echo "✓ Config is valid JSON"

# Check threat model has key sections
grep -q "## 1. System Overview" .factory/threat-model.md && echo "✓ Has System Overview"
grep -q "## 5. Threat Analysis" .factory/threat-model.md && echo "✓ Has Threat Analysis"
grep -q "## 6. Vulnerability Pattern Library" .factory/threat-model.md && echo "✓ Has Pattern Library"

Example Invocations

Generate initial threat model:

Generate a threat model for this repository using the threat-model-generation skill.

Update existing threat model after architecture change:

Update the threat model - we added a new payments service in services/payments/.

Generate with compliance requirements:

Generate a threat model for this repository. We need to comply with SOC2 and GDPR.

References

平台分布

Codex

36.89%
按下载量换算111

Claude

27.1%
按下载量换算82

Cursor

20.7%
按下载量换算62

Gemini CLI

10.1%
按下载量换算30

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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