Netw0rkNoob
Netw0rkNoob/VulnClaw
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/Netw0rkNoob/VulnClaw --skill ai-mcp-security命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | ai-mcp-security |
| description | AI与MCP安全评估 — Prompt注入、工具滥用、MCP信任边界、Agent权限逃逸、数据泄露、模型风险、GAARM风险矩阵 |
| routing | {"target_types":["ai_agent","mcp"],"task_types":["pentest","audit"],"technologies":["llm","rag","memory","plugin"],"vulnerability_classes":["prompt_injection","tool_abuse","info_disclosure"]} |
当目标包含 LLM、Agent、MCP 工具、Skills、RAG、Memory、Plugin 或模型服务组件时使用本 Skill。
前置条件：如果 AI 表面只是展示层，真正的阻塞仍是客户端签名或加密协议，先回到 client-reverse Skill。
| 风险类型 | 首选参考 |
|---|---|
| Prompt 注入 / 间接注入 / CoT 干扰 | references/ai-app-security.md |
| 工具滥用 / MCP 投毒 / Skills 供应链 | references/04-ai-and-mcp-security-integrated.md MCP 章节 |
| 权限逃逸 / 角色越界 / 凭据滥用 | references/ai-identity-security.md |
| 数据泄露 / Prompt 泄漏 / 模型逆推 | references/ai-data-security.md |
| 容器逃逸 / CI-CD / 沙箱失败 | references/ai-baseline-security.md |
| 模型风险 / 对抗样本 / 后门 | references/ai-model-security.md |
| 影响分类与覆盖评估 | references/gaarm-risk-matrix.md |
references/04-ai-and-mcp-security-integrated.md — AI 与 MCP 安全整合参考references/ai-app-security.md — AI 应用安全references/ai-identity-security.md — AI 身份安全references/ai-data-security.md — AI 数据安全references/ai-baseline-security.md — AI 基线安全references/ai-model-security.md — AI 模型安全references/gaarm-risk-matrix.md — GAARM 风险矩阵OSINT 开源情报收集知识库 — 四维信息收集模型（服务器→网站→域名→人员），维度四（人员信息）条件触发
Domain routing and boundary guidance for authorized Active Directory red-team security testing, including Kerberos attacks, domain privilege escalation, lateral movement, and GPO abuse. Use when a task belongs to the AD testing domain and needs scope, evidence, pivot, or exit criteria.
Domain routing and boundary guidance for authorized API security testing, including BOLA/IDOR, authentication bypass, mass assignment, missing rate limits, and GraphQL issues. Use when a task belongs to the API testing domain and needs scope, evidence, pivot, or exit criteria.
基于 SOC 职业分类