MISP MCP Server

A Model Context Protocol server for MISP (Malware Information Sharing Platform), with built-in prompt injection defense powered by prompt-defense-audit.

Why this exists: MISP holds operational threat intel — IOCs, threat actor profiles, attack patterns. When you connect an LLM agent to MISP via MCP, two new attack surfaces emerge:

1. Adversarial seeding. A threat actor who can submit content into your MISP instance (or a federated feed) can plant prompt-injection payloads designed to hijack downstream LLM agents.

2. Sensitive intel leakage. A manipulated LLM can be coerced into returning intel above its authorized TLP level.

This server wraps every outgoing MISP response in prompt-defense-audit's output scanner, blocking high-risk patterns before they reach the LLM. Read-only by design — no write tools exposed.

Tracks: MISP/MISP#10745 — MCP server for MISP

Features

• 🛡️ Defense built in — every MISP response scanned for prompt-injection / XSS / shell-injection patterns before being returned

• 🔒 Read-only by design — no event/attribute mutation tools; an LLM cannot modify your threat-intel platform

• 🧰 8 high-utility tools covering events, attributes, search, tags, feeds, galaxies

• ⚡ Zero-config beyond MISP_URL and MISP_API_KEY

• 🪶 Stdio transport — works with Claude Desktop, Cursor, Continue, Cline, any MCP client

• 📋 MIT license — fork freely, use commercially

Related MCP server: llmprobe

Quick start

1. Install

npm install -g @ultralab/misp-mcp-server

Or use npx directly in your MCP client config (no install needed).

2. Configure your MCP client

Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%/Claude/claude_desktop_config.json on Windows):

{
  "mcpServers": {
    "misp": {
      "command": "npx",
      "args": ["-y", "@ultralab/misp-mcp-server"],
      "env": {
        "MISP_URL": "https://misp.your-org.example",
        "MISP_API_KEY": "your_misp_api_key_here"
      }
    }
  }
}

Cursor / Continue / Cline — similar pattern, see your client's MCP config docs.

3. Restart your MCP client and start asking

"What MISP events are tagged tlp:white from the last 7 days?"
"Show me event 12345 — I'm investigating a phishing report."
"What threat actor galaxies do we have configured?"
"Find all attributes matching the IP 198.51.100.42."

Tools exposed

Mutation tools intentionally not included. An LLM with write access to MISP is a supply-chain compromise vector. If you need agent-driven MISP mutations, build a per-tool allowlist with human-in-the-loop confirmation.

Defense layer

Every tool response is run through prompt-defense-audit's scanOutput before being returned to the LLM client.

High-risk patterns (critical / high severity) — response is blocked and replaced with a safe summary. Example trigger patterns:

• Script-tag injection (<script>...</script>)

• Iframe / object injection

• JavaScript URLs (javascript:)

• Shell-command patterns in unexpected contexts

• Known prompt-injection vector signatures from prompt-defense-audit's 17+ vector library

Low/medium-risk patterns — response annotated with a [defense] prefix listing matched patterns but still returned.

Opt out (not recommended)

PROMPT_DEFENSE_DISABLED=true

Use only if you fully trust your MISP instance + all federated feeds and need raw response fidelity for a specific debugging scenario.

Environment variables

For enterprise users

The free OSS defense layer ships with prompt-defense-audit (17+ regex-based vectors, ~3ms latency, deterministic).

For deployments that need:

• 🔍 Persistent audit logs of every MISP query an LLM has made

• 👥 Team policies (per-role allowlists, per-TLP gating, escalation flows)

• 🌏 Jurisdictional compliance (EU GDPR / TW 個資法 / 中國 PIPL data-residency)

• 🚨 Live threat intel updates to the defense ruleset (new injection vectors pushed daily)

• 📊 SLA-backed uptime and response

→ Upgrade path: route MCP server through Quartz Cloud — Taiwan-domiciled runtime AI firewall, drop-in passthrough.

Development

git clone https://github.com/ppcvote/misp-mcp-server.git
cd misp-mcp-server
npm install
npm test            # smoke tests, no live MISP
npm run dev         # tsx watch mode
npm run build       # produce dist/

Architecture

LLM client (Claude Desktop, Cursor, etc.)
    │ stdio
    ▼
@ultralab/misp-mcp-server
    │
    ├─ src/tools.ts       — 8 read-only tool definitions + dispatch
    ├─ src/misp-client.ts — minimal MISP REST API wrapper
    └─ src/index.ts       — MCP Server + scanOutput() defense layer
    │
    ▼
MISP REST API (/events, /attributes, /tags, /feeds, /galaxies)

Project context

Built by Ultra Lab — a one-person AI products company in Taiwan, focused on AI safety, threat intel, and the supply chain between LLM agents and operational security tooling.

This server is part of a broader thesis: the MCP ecosystem will be a major prompt-injection vector unless servers default to defensive output handling. We're shipping reference implementations for high-leverage targets (MISP first, OpenCTI / TheHive / Vault next) to anchor the standard.

Companion projects:

• prompt-defense-audit — the underlying detection engine

• ultraprobe — CLI scanner for AI app system prompts

• quartz.tw — paid runtime firewall (audit logs, team policies, jurisdictional moat)

License

MIT © 2026 Ultra Lab — see LICENSE.

Contributing

PRs welcome. Please:

1. Keep the read-only invariant. Mutation tools must be argued explicitly with a threat-model writeup.

2. Add a test for any new tool.

3. If you add new MISP API coverage, link to the relevant OpenAPI spec section in your PR.

For discussion, see MISP/MISP#10745.