🔮 未来使用 MCP 和 AI 的工作

1. 自主红队特工 构建由LLM驱动的代理，自主执行侦察、有效载荷生成、利用和报告，所有这些都通过MCP工具进行编排。

2. AI驱动的SOC分析师 整合 Wazuh + Suricata + Zeek 日志，并使用 MCP 让 Claude 实时分析事件、检测横向移动并推荐响应措施。

3. 恶意软件开发工作室（LLM + MCP） 使用 Claude + MCP 通过 Capstone、Donut 和 Sliver 等工具，自动生成 shellcode 生成、混淆、沙箱规避和绕过 EDR 策略。

4. 威胁狩猎自动化 开发主动的AI工作流程，分析日志、关联指标，并基于MCP resources和tools的威胁情报源进行搜寻。

5. 基于代理的紫色团队模拟器 将MCP与ATT&CK模拟结合，Claude负责协调红方和蓝方的双方技术（原子红队、Caldera、Sigma/YARA规则生成）。

6. CI/CD + DevSecOps 集成 使用MCP审查推送到GitHub的代码，扫描秘密，触发安全工具（Trufflehog、Gitleaks），并发送安全警报或PR建议。

Offensive-MCP-AI

🔮 Future Work Using MCP and AI

1. Autonomous Red Team Agents
   Build LLM-driven agents that autonomously conduct reconnaissance, payload generation, exploitation and reporting, all orchestrated via MCP tools.

2. AI-Powered SOC Analyst
   Integrate Wazuh + Suricata + Zeek logs and use MCP to let Claude analyze incidents, detect lateral movement, and recommend response actions in real-time.

3. Malware Dev Studio (LLM + MCP)
   Use Claude + MCP to automate shellcode generation, obfuscation, sandbox evasion, and EDR bypass strategies through tools like Capstone, Donut, and Sliver.

4. Threat Hunting Automation
   Develop proactive AI workflows that analyze logs, correlate indicators, and hunt based on threat intelligence feeds via MCP resources and tools.

5. Agent-Based Purple Team Simulator
   Combine MCP with ATT&CK simulations, where Claude orchestrates both Red and Blue side techniques (Atomic Red Team, Caldera, Sigma/YARA rule generation).

6. CI/CD + DevSecOps Integration
   Use MCP to review code pushed to GitHub, scan secrets, trigger security tools (Trufflehog, Gitleaks), and send secure alerts or PR recommendations.

7. Auto Incident Report Generator
   Claude consumes logs and tool outputs via MCP and generates full incident reports (including diagrams and mitigations) in Markdown or PDF formats.

8. Cybersecurity Tutor / Trainer Mode
   Claude explains what each tool does, simulates attacks in safe lab environments, and evaluates user responses via MCP simulation tools.

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🔗 Installation & Integration Links

✅ Install MCP CLI and SDK (Python)

pip install modelcontextprotocol

Docs:
🔗 https://modelcontextprotocol.io/quickstart/server
GitHub:
🔗 https://github.com/jlowin/fastmcp

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🧠 Claude Desktop Configuration (Mac, Linux, Windows)

1. Install Claude for Desktop
   🔗 https://www.anthropic.com/index/claude-desktop

2. Edit config file:

macOS/Linux

nano ~/Library/Application\ Support/Claude/claude_desktop_config.json

Windows

notepad %AppData%\Claude\claude_desktop_config.json

3. Add your MCP server:

{
  "mcpServers": {
    "my-wazuh-agent": {
      "command": "/full/path/to/python",
      "args": [
        "mcp_wazuh_server.py"
      ]
    }
  }
}

4. Restart Claude Desktop — you’ll see the connector icon (⚡) for prompts and the tools icon (🛠) for tool invocation.

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🧪 Test Locally with Inspector

Run your server with debugging:

npx @modelcontextprotocol/inspector python mcp_wazuh_server.py

This opens a local UI where you can test @mcp.tool() and @mcp.prompt() before linking with Claude.