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attack-surface攻击面

Agent Skill

attack-surface 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

总安装

285

周安装

12

GitHub Stars

9

下载量

167
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:attack-surface(攻击面)
来源仓库:https://github.com/florianbuetow/claude-code
仓库路径:skills/attack-surface
安装命令:
npx skills add https://github.com/florianbuetow/claude-code --skill attack-surface
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/florianbuetow/claude-code --skill attack-surface

简介

attack-surface 用于扫描应用程序的攻击面,识别所有外部数据接口与输入入口点。

  • 适用于安全审计、渗透测试前期侦察及合规性检查等高阶防护场景。
  • 按风险等级组织路由、API 端点与信任边界,输出可操作的加固建议清单。
  • 支持细粒度作用域控制,但窄范围扫描会发出警告提示完整性不足。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Attack Surface Mapping

Discover and inventory every entry point where external data enters the application. Produces a ranked catalog of all routes, APIs, input handlers, and external interfaces organized by exposure level and trust boundary.

Supported Flags

Read ../../shared/schemas/flags.md for the full flag specification.

FlagAttack Surface Behavior
--scopeDefault full. Attack surface mapping benefits from whole-codebase visibility. Narrow scopes produce partial inventories with a warning.
--depth quickFramework route extraction only (Grep for route decorators and definitions).
--depth standardRoute extraction + read handlers to classify input types and auth requirements.
--depth deepStandard + trace each entry point to internal sinks, map trust boundary crossings.
--depth expertDeep + rank by exploitability, identify shadow/undocumented endpoints, DREAD scoring.
--severityNot directly applicable. Used to filter the exposure ranking in output.
--formatDefault text. Use json for machine-readable inventory, md for wiki export.

Workflow

Step 1: Determine Scope

  1. Parse --scope flag. Default to full for this skill (attack surface requires broad visibility).
  2. Resolve to a concrete file list.
  3. Prioritize discovery in: route files, controller directories, API definitions, middleware, OpenAPI/Swagger specs, GraphQL schemas, gRPC proto files, CLI entry points, WebSocket handlers.

Step 2: Discover Framework and Language

Identify the application framework(s) to determine route registration patterns:

FrameworkRoute Pattern
Express/Koa/Fastifyapp.get(), router.post(), fastify.route()
Djangourlpatterns, path(), re_path(), @api_view
Flask@app.route(), @blueprint.route()
Spring@GetMapping, @PostMapping, @RequestMapping
Railsroutes.rb, resources:, get '/'
Next.js/Nuxtpages/ and app/ directory conventions, route.ts
ASP.NET[HttpGet], [Route], MapGet(), MapPost()
Go net/httphttp.HandleFunc(), mux.Handle(), gorilla/chi patterns
FastAPI@app.get(), @router.post()
gRPC.proto service definitions, generated server stubs
GraphQLSchema definitions, resolver registrations

Step 3: Extract Entry Points

For each framework detected, systematically extract all entry points:

  1. HTTP Routes: Method, path, handler function, middleware chain.
  2. API Endpoints: REST, GraphQL queries/mutations, gRPC services.
  3. Form Handlers: HTML form action targets, multipart upload handlers.
  4. File Upload Endpoints: Endpoints accepting file data, storage destinations.
  5. WebSocket Handlers: Connection endpoints, message handlers.
  6. CLI Arguments: Argument parsers (argparse, commander, cobra, clap).
  7. Message Queue Consumers: Kafka/RabbitMQ/SQS message handlers.
  8. Scheduled Tasks: Cron jobs, scheduled functions that process external data.
  9. Webhook Receivers: Endpoints accepting callbacks from external services.
  10. Server-Sent Events: SSE endpoints, streaming responses.

Step 4: Classify Each Entry Point

For every discovered entry point, determine:

  1. Authentication: None, API key, session, JWT, OAuth, mTLS, or unknown.
  2. Authorization: None, role-based, attribute-based, or unknown.
  3. Input Types: Query params, path params, headers, body (JSON/XML/form), files, cookies.
  4. Validation: Present (with details) or absent.
  5. Rate Limiting: Present or absent.
  6. Network Exposure: Internet-facing, internal network, localhost only.
  7. Protocol: HTTP, HTTPS, WebSocket, gRPC, raw TCP, message queue.

Step 5: Rank by Exposure

Assign an exposure level to each entry point:

LevelCriteria
CRITICALInternet-facing, no authentication, accepts user input, interacts with sensitive data or system resources
HIGHInternet-facing with authentication but handling sensitive data, or unauthenticated endpoints with limited input validation
MEDIUMAuthenticated endpoints with proper validation, or internal endpoints with no authentication
LOWInternal endpoints with authentication, limited input surface, or read-only operations on non-sensitive data

At --depth deep and --depth expert, trace each HIGH/CRITICAL entry point inward to identify what sinks they reach (databases, file system, external services, system commands).

Step 6: Identify Shadow Endpoints

At --depth expert, look for:

  • Debug/admin routes not behind auth middleware (e.g., /debug, /admin, /metrics, /health exposing internals).
  • Routes registered dynamically or via reflection that don't appear in static route lists.
  • Endpoints in test/staging configuration that may be active in production.
  • API versions that are deprecated but still routed.
  • OpenAPI/Swagger UI exposed without authentication.

Step 7: Report

Output the attack surface inventory.

Output Format

This skill produces an inventory, not vulnerability findings. However, when entry points have clearly missing security controls (no auth on sensitive endpoints), emit findings using the standard schema from ../../shared/schemas/findings.md.

Finding ID prefix: SURF (e.g., SURF-001).

Inventory Table

## Attack Surface Inventory

### Summary
- Total entry points: N
- Internet-facing: N (N unauthenticated)
- Internal: N
- Exposure: N CRITICAL, N HIGH, N MEDIUM, N LOW

### Entry Points by Exposure

| # | Method | Path | Auth | Input Types | Validation | Rate Limit | Exposure |
|---|--------|------|------|-------------|------------|------------|----------|
| 1 | POST | /api/v1/users | None | JSON body | None | No | CRITICAL |
| 2 | GET | /api/v1/users/:id | JWT | Path param | Partial | Yes | MEDIUM |
| ... |

### Trust Boundary Map (--depth deep)
[Mermaid diagram showing entry points grouped by trust boundary]

### Shadow Endpoints (--depth expert)
[Undocumented or debug endpoints discovered]

### Findings
[Standard findings for missing security controls on entry points]

Findings follow ../../shared/schemas/findings.md with:

  • metadata.tool: "attack-surface"
  • metadata.framework: depends on invoking context (or null if standalone)
  • references.cwe: CWE-16 (Configuration), CWE-306 (Missing Authentication)

Pragmatism Notes

  • Health check endpoints (/health, /ready) without auth are normal in container orchestration. Only flag if they expose sensitive internal state.
  • Internal APIs behind a service mesh or VPN still warrant inventory but at lower exposure.
  • CLI tools that only run locally have minimal attack surface unless they parse untrusted files.
  • Static file serving endpoints are low priority unless directory traversal is possible.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.01%
按下载量换算60

Claude

28.65%
按下载量换算48

Cursor

17.19%
按下载量换算29

Gemini CLI

9.7%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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