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Wazuh-Openclaw-Autopilot

mcp
SUMMARY

Autonomous SOC layer for Wazuh using OpenClaw agents with MCP . Auto-triage alerts, correlate incidents, generate response plans with human-in-the-loop approval. Evidence packs, Prometheus metrics, Slack integration.

README.md

Wazuh OpenClaw MCP

Wazuh OpenClaw Autopilot

Turn your Wazuh SIEM into an autonomous SOC with AI agents that triage, investigate, and respond — while humans stay in control.

Release License: MIT CI Issues Stars

Quick Start · How It Works · Deploy · API Docs · Changelog

What It Does

A Wazuh alert fires. Within minutes — not hours — your SOC has:

  1. Triaged the alert with entity extraction, MITRE mapping, and severity assessment
  2. Correlated it with related alerts across hosts, IPs, and users
  3. Investigated via live Wazuh queries — auth history, process trees, lateral movement checks
  4. Generated a response plan with risk assessment and rollback procedures
  5. Executed the response (IP block, host isolation, process kill) — only after human approval

No alert sits unread. No playbook gets skipped. Every action has an evidence trail.

Before and After

Without Autopilot With Autopilot
Alert triage Manual review, 15-60 min per alert Automatic, ~40 seconds
Investigation Analyst runs queries, cross-references 7+ pivot queries run automatically
Response Find playbook, execute manually Risk-assessed plan, one-click approve
Evidence Scattered across tools Structured JSON evidence pack per case
Coverage Business hours, analyst availability 24/7, every alert processed

How It Works

  Wazuh Alert
       │
       ▼
  ┌─────────┐    ┌─────────────┐    ┌───────────────┐    ┌──────────────┐
  │ Triage  │───▶│ Correlation │───▶│ Investigation │───▶│   Response   │
  │  Agent  │    │    Agent    │    │    Agent      │    │   Planner    │
  └─────────┘    └─────────────┘    └───────────────┘    └──────┬───────┘
   Extract IOCs   Group related      Query Wazuh via       Generate plan
   Map MITRE       alerts into        MCP (48 tools)       Assess risk
   Set severity    unified cases      Build timeline       Assign actions
                                                                │
                                                                ▼
                                                     ┌──────────────────┐
                                                     │  Policy Guard    │
                                                     │  + Human Review  │
                                                     └────────┬─────────┘
                                                              │
                                                     [Approve] [Reject]
                                                              │
                                                              ▼
                                                     ┌──────────────────┐
                                                     │   Responder      │
                                                     │   (Execution)    │
                                                     └──────────────────┘
                                                      block_ip, isolate_host,
                                                      kill_process, disable_user...

7 specialized agents work as a pipeline. Each agent has a single responsibility, its own playbook, and communicates through the runtime service via webhooks. The runtime enforces policy at every step — action allowlists, confidence thresholds, rate limits, time windows, and idempotency checks.

AI agents never act autonomously. Every response action requires explicit two-tier human approval (Approve + Execute). The responder capability is disabled by default.

Key Features

Detection & Analysis

  • Autonomous alert triage with entity extraction (IPs, users, hosts, hashes)
  • MITRE ATT&CK technique and tactic mapping
  • Entity-based alert grouping into unified cases
  • AbuseIPDB IP reputation enrichment with TTL caching
  • Investigation agent runs 7+ pivot queries per case via Wazuh MCP Server (48 tools)

Response & Enforcement

  • Risk-assessed response plans with rollback metadata
  • 9 Wazuh Active Response actions (block IP, isolate host, kill process, disable user, quarantine file, firewall drop, host deny, restart, generic AR)
  • Inline policy enforcement: action allowlists, confidence thresholds, approver authorization, evidence requirements, time windows, rate limits, idempotency
  • Two-tier approval workflow with separation of duties

Observability & Reporting

  • Structured JSON evidence packs for compliance and forensics
  • Prometheus metrics with SOC KPIs (MTTD, MTTT, MTTI, MTTR, MTTC)
  • KPI endpoint with SLA compliance tracking
  • Reporting agent generates hourly, daily, weekly, and monthly SOC health reports
  • Slack integration with real-time alerts and interactive approval buttons (Socket Mode)

Operations

  • Crash recovery for plans stuck mid-execution
  • Stalled pipeline detection with automatic re-dispatch
  • Alert dedup across date boundaries
  • LLM type coercion for local model compatibility
  • Investigation findings auto-promoted to case severity/confidence

Quick Start

Prerequisites

Requirement Description
Wazuh 4.8+ SIEM platform, installed and running
Wazuh MCP Server v4.2.1+ MCP bridge for Wazuh API (48 tools)
OpenClaw v2026.7.3+ AI agent framework
Node.js 20+ Runtime service (22+ recommended)
LLM API Key Claude, GPT, Groq, Mistral, or local Ollama/vLLM

Install

git clone https://github.com/gensecaihq/Wazuh-Openclaw-Autopilot.git
cd Wazuh-Openclaw-Autopilot
sudo ./install/install.sh

The installer handles MCP Server setup, OpenClaw configuration, agent deployment, and optional Slack integration. For air-gapped environments, use --mode bootstrap.

Configure

sudo nano /etc/wazuh-autopilot/.env

# Wazuh connection
WAZUH_HOST=localhost
WAZUH_PORT=55000
WAZUH_USER=wazuh-wui
WAZUH_PASS=your-password

# LLM provider (pick one — we recommend OpenRouter for simplicity)
OPENROUTER_API_KEY=sk-or-...

# Optional: Slack approval buttons
SLACK_APP_TOKEN=xapp-...
SLACK_BOT_TOKEN=xoxb-...

Verify

curl http://localhost:9090/health
curl http://localhost:9090/metrics

Deployment Options

Method Best For Command
Docker Compose Production docker-compose up -d
Systemd Native Linux sudo ./install/install.sh
Air-gapped Classified / offline sudo ./install/install.sh --mode bootstrap + guide
vLLM Self-hosted GPU vLLM Guide
Manual Development cd runtime/autopilot-service && npm start

LLM Providers

OpenClaw is model-agnostic. Use any provider:

Provider Best For Cost
OpenRouter Safest option — 300+ models, single key, no ban risk Pay per token
Anthropic Best reasoning (Claude) Pay per token
Groq Ultra-fast inference Free tier available
Ollama Air-gapped / free Free (local)
vLLM Self-hosted GPU inference Hardware only

Plus OpenAI, Google, Mistral, xAI, Together, Cerebras. See full provider guide below.

API Keys Only: Use pay-per-token API keys, not subscription OAuth tokens. Anthropic and Google have banned subscription tokens in third-party tools. Details.

Human-in-the-Loop Approval

 PROPOSED ────▶ APPROVED ────▶ EXECUTED
    │               │               │
    ▼               ▼               ▼
 Policy Check   Policy Check    Policy Check
 ─ allowlist    ─ approver ID   ─ evidence
 ─ confidence   ─ risk level    ─ time window
 ─ time window                  ─ rate limit
                                ─ idempotency

AI agents generate plans. Humans approve them. The runtime enforces policy at every step. No action executes without human authorization.

Wazuh Compatibility

Tested via Wazuh MCP Server v4.2.1 (48 tools):

Wazuh Version Status
4.14.x Fully Supported (recommended)
4.8.x – 4.13.x Fully Supported
4.0.0 – 4.7.x Limited (no vulnerability tools)

Platforms: Ubuntu 22.04/24.04, Debian 11/12, RHEL/Rocky/AlmaLinux 8/9, Docker.

API Reference

Core Endpoints

Endpoint Method Description
POST /api/alerts POST Ingest Wazuh alert — triggers full pipeline
GET /api/cases GET List cases (filter: ?status=, ?severity=, ?since=, ?until=)
GET /api/cases/summary GET Aggregated case statistics
GET /api/cases/:id GET Full case with evidence pack
GET /api/plans GET List plans (filter: ?state=, ?case_id=)
GET /api/plans/:id GET Plan details
POST /api/plans/:id/approve POST Approve plan (Tier 1)
POST /api/plans/:id/execute POST Execute plan (Tier 2)
GET /api/kpis GET SLA/KPI metrics (?period=24h)
GET /api/reports GET List stored reports
GET /metrics GET Prometheus metrics

Agent Action Endpoints (GET-based for web_fetch)

Endpoint Description
/api/agent-action/update-case Update case status/data
/api/agent-action/create-plan Create response plan
/api/agent-action/approve-plan Approve/deny plan
/api/agent-action/execute-plan Execute approved plan
/api/agent-action/store-report Store generated report
/api/agent-action/search-alerts Proxy search to Wazuh MCP

Full API documentation: RUNTIME_API.md

SOC KPIs & Reporting

The runtime tracks case status transitions and computes SLA metrics:

curl http://localhost:9090/api/kpis?period=24h

{
  "period": "24h",
  "cases_analyzed": 50,
  "mttt": 42,
  "mtti": 138,
  "mttr": 280,
  "mttc": 450,
  "auto_triage_rate": 0.92,
  "false_positive_rate": 0.18,
  "sla_compliance": {
    "triage_within_15m": 0.95,
    "response_within_1h": 0.82
  }
}

The reporting agent generates hourly, daily, weekly, and monthly SOC health reports automatically.

Evidence Packs

Every case produces a structured evidence pack for compliance and forensics:

{
  "case_id": "CASE-20260327-1df903b68bc7",
  "severity": "high",
  "confidence": 0.95,
  "entities": [
    {"type": "ip", "value": "176.120.22.47", "role": "source"},
    {"type": "host", "value": "virt-5378", "role": "victim"}
  ],
  "mitre": [{"technique_id": "T1110.001", "tactic": "Credential Access"}],
  "investigation_notes": "200+ failed SSH login attempts over 7 days...",
  "findings": {"classification": "brute_force", "confidence": 0.95},
  "status_history": [
    {"from": "open", "to": "triaged", "timestamp": "..."},
    {"from": "triaged", "to": "investigated", "timestamp": "..."}
  ],
  "plans": [...],
  "actions": [...],
  "mcp_calls": [...]
}

Security

Layer Protection
Network All services localhost-only. Tailscale zero-trust for inter-node.
Auth Bearer token + query param auth. Timing-safe comparison.
Policy Inline enforcement at every pipeline step. Fail-closed in production.
Agents Sandboxed execution. Anti-injection instructions. No exec access.
Approval Two-tier human approval. Separation of duties. Bootstrap gate requires explicit opt-in.
MCP RBAC scopes (wazuh:read/wazuh:write). JWT auth. Circuit breaker.

Slack Integration

Socket Mode — outbound-only, no webhooks or public endpoints required:

  • Real-time alert notifications with severity coloring
  • Interactive [Approve] / [Reject] / [Execute] buttons
  • Slash commands: /wazuh status, /wazuh approve, /wazuh execute
  • Confirmation dialogs for destructive actions

Project Structure

├── install/install.sh              # Security-hardened installer
├── docker-compose.yml              # Production container orchestration
├── openclaw/
│   ├── openclaw.json               # Gateway & model config
│   └── agents/                     # 7 SOC agents (AGENTS.md, TOOLS.md, IDENTITY.md)
├── runtime/autopilot-service/
│   ├── index.js                    # Runtime service (6400+ LOC)
│   ├── slack.js                    # Slack Socket Mode integration
│   └── *.test.js                   # 532 tests across 15 files
├── policies/
│   ├── policy.yaml                 # Action allowlists, approvers, thresholds
│   └── toolmap.yaml                # MCP tool mappings (9 action tools)
├── playbooks/                      # 7 incident response playbooks
└── docs/                           # 15 documentation files

Local LLM Options

Ollama (Air-Gapped)

Zero external network calls. Full data sovereignty. See Air-Gapped Guide.

sudo ./install/install.sh --mode bootstrap

vLLM (Self-Hosted GPU)

Production-grade throughput with open-source models. See vLLM Guide.

vllm serve Qwen/Qwen3-32B --enable-auto-tool-choice --tool-call-parser hermes
Model VRAM Best For
Qwen3 32B ~64 GB Best tool calling
Llama 3.3 70B ~140 GB Strongest reasoning
DeepSeek-R1 70B ~140 GB Chain-of-thought

Provider Details

Full provider list and configuration
Provider Models API Key Env
OpenRouter 300+ models OPENROUTER_API_KEY
Anthropic Claude Sonnet 4.5, Haiku 4.5 ANTHROPIC_API_KEY
OpenAI GPT-4o, o3-mini OPENAI_API_KEY
Groq Llama 3.3 70B, Mixtral GROQ_API_KEY
Google Gemini 2.0 Flash/Pro GOOGLE_API_KEY
Mistral Mistral Large, Codestral MISTRAL_API_KEY
xAI Grok 2, Grok 3 XAI_API_KEY
Ollama Llama, Mistral, Qwen N/A (local)
vLLM Any HuggingFace model VLLM_API_KEY
Together Open-source models TOGETHER_API_KEY
Cerebras Ultra-fast inference CEREBRAS_API_KEY

Model format: "provider/model-name" (e.g., "anthropic/claude-sonnet-4-5").

Cost Optimization

Task Recommended Model Why
Complex investigation anthropic/claude-sonnet-4-5 Best reasoning
High-volume triage groq/llama-3.3-70b-versatile Fast and free
Heartbeats anthropic/claude-haiku-4-5 Cheapest Claude
Air-gapped ollama/llama3.3 No network
GPU self-hosted vllm/qwen3-32b Best open-source tool calling

Provider Policy Notice

Important: API keys vs subscription tokens

Anthropic and Google have banned subscription-plan OAuth tokens (Claude Pro/Max, Google AI Ultra) in third-party tools. Using them will result in account suspension.

Always use pay-per-token API keys from the provider's developer console, or route through OpenRouter (billing proxy, no ban risk).

  • OpenRouter: Single key, 300+ models, no restrictions
  • Groq, Mistral, xAI, Together, Cerebras: No restrictions reported

Documentation

Document Description
QUICKSTART.md Installation guide
RUNTIME_API.md REST API reference
POLICY_AND_APPROVALS.md Policy engine and approval workflow
SLACK_SOCKET_MODE.md Slack setup
EVIDENCE_PACK_SCHEMA.md Evidence pack format
AGENT_CONFIGURATION.md Agent customization
AIR_GAPPED_DEPLOYMENT.md Offline deployment with Ollama
VLLM_DEPLOYMENT.md GPU inference with vLLM
MCP_INTEGRATION.md MCP server integration
AGENT_COMMUNICATION.md Agent-to-runtime architecture
TROUBLESHOOTING.md Common issues and fixes
CHANGELOG.md Version history

Contributing

cd runtime/autopilot-service
npm install
npm test   # 532 tests, all passing

See CONTRIBUTING.md for guidelines.

Community

Related Projects

Project Description
Wazuh MCP Server MCP bridge for Wazuh API (48 tools, RBAC, audit logging)
OpenClaw AI agent framework powering the SOC agents

License

MIT License — see LICENSE

Built by GenSecAI

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