firewall-aiops

firewall-aiops

Governed OPNsense + pfSense firewall operations — gateway-health, rule-shadow, and blocked-traffic RCA, with guarded rule/alias writes, unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

Category
Visit Server

README

<!-- mcp-name: io.github.AIops-tools/firewall-aiops -->

Firewall AIops

Governed, audited AI-ops for OPNsense and pfSense firewalls — for AI agents (via MCP) and humans (via CLI).

Disclaimer: Community-maintained open-source project. Not affiliated with, endorsed by, or sponsored by the OPNsense project, Deciso, Netgate, or the pfSense project. OPNsense, pfSense and Netgate are trademarks of their respective owners. MIT licensed.

firewall-aiops speaks to two firewall platforms behind one MCP server — OPNsense (REST API under /api/..., API key+secret via HTTP Basic auth) and pfSense (REST API v2 under /api/v2/... from the pfSense-pkg-RESTAPI package, API key via an X-API-Key header) — with the same tools working on both. Each target in the config names its own platform; a name-keyed platform registry selects the API shape (auth + resource paths), so an agent never has to know which firewall it is talking to.

Every tool runs through a built-in governance harness (vendored, zero external dependency): audit log, token/call budget with runaway circuit-breaker, descriptive risk-tier labelling, undo-token recording, and prompt-injection sanitisation.

Why this exists

  • One server, both firewalls — OPNsense and pfSense in a mixed estate, spoken to through identical tool names. Adding a third firewall later is a new platform descriptor, not a rewrite.
  • Read the whole firewall — firmware/health, interfaces & gateways, filter rules (with hit counts and state table), NAT (port-forward / outbound / 1:1), aliases, VPN (WireGuard / OpenVPN / IPsec), DHCP leases & reservations, and the firewall log.
  • Flagship RCA analyses — transparent heuristics that show their numbers, never a black-box verdict: gateway_health_rca (WAN loss/latency/down → cause + action), rule_hit_and_shadow_analysis (never-hit + shadowed/redundant rules), and blocked_traffic_rca (top blocked sources/ports → scan / brute-force / probe).
  • Governed writes — toggle a rule, add/remove an alias entry (reversible, undo-recorded from the fetched before-state), flush states, restart a service, and the "make it live" commit (apply_changes / reconfigure) and reboot at risk=high with a dry-run preview. Every write, reversible or not, lands an audit row.

What this tool does, and does not, decide

It delivers firewall operations — reads and writes — accurately and efficiently, and records every one of them. It does not decide whether a write is allowed to happen. That is the agent's judgement, or the permission of the account you connect it with: give the OPNsense/pfSense API user a read-only role, and the writes fail at the server — the place that actually owns the permission.

So there is no read-only switch, no policy file, no approval gate to configure. The one thing the tool guarantees is that nothing is silent: every call, over MCP and over the CLI alike, lands an audit row in ~/.firewall-aiops/audit.db, and reversible writes still capture their before-state and record an inverse where one exists.

Each tool declares a risk_level, matched to its [READ]/[WRITE] documentation tag, and carried into the audit row as a descriptive tier — so a reviewer can see at a glance that a row was a high-risk write. It is a label, not a gate.

Running a smaller / local model? See agent-guardrails.md — it lists the guardrails this tool now enforces for you (so you don't spend prompt budget restating them) and gives a ready-made system prompt for what's left.

Tool inventory (35 tools)

Domain Tools # Kind
System firmware_status, health_status, interface_status, gateway_status 4 read
Rules list_rules, rule_detail, rule_stats, rule_states 4 read
NAT nat_port_forwards, nat_outbound, nat_one_to_one 3 read
Aliases list_aliases, alias_entries 2 read
VPN wireguard_status, openvpn_sessions, ipsec_sas 3 read
DHCP dhcp_leases, dhcp_static_mappings 2 read
Diagnostics firewall_log, states_table, top_talkers 3 read
Flagship analyses gateway_health_rca, rule_hit_and_shadow_analysis, blocked_traffic_rca 3 read
Writes toggle_rule, add_alias_entry, remove_alias_entry, kill_states, restart_service 5 write (med)
Writes apply_changes, reconfigure, reboot 3 write (high)
Undo undo_list, undo_apply 2 read / write

Reversible writes record an inverse undo descriptor built from the real fetched before-state (toggle_rule restores the rule's prior enabled flag; alias add/remove invert). apply_changes / reconfigure / reboot are high-risk with dry_run; reboot is irreversible (audit only).

Install

uv tool install firewall-aiops        # or: pipx install firewall-aiops

Quick start

firewall-aiops init                     # wizard: pick platform (opnsense/pfsense) + store the secret (encrypted)
firewall-aiops doctor                   # verify config, secrets, and connectivity
firewall-aiops overview                 # one-shot: version + gateway/interface health + rule count
firewall-aiops rules list               # list filter rules
firewall-aiops rules toggle <uuid> --disable   # dry-run + double-confirm governed write
firewall-aiops log --action block -n 50 # recent blocked traffic

Run the MCP server (stdio) for an agent:

firewall-aiops mcp                      # or: firewall-aiops-mcp

MCP client config

{
  "mcpServers": {
    "firewall-aiops": {
      "command": "uvx",
      "args": ["--from", "firewall-aiops", "firewall-aiops-mcp"],
      "env": { "FIREWALL_AIOPS_MASTER_PASSWORD": "your-master-password" }
    }
  }
}

Configuration

~/.firewall-aiops/config.yaml (non-secret connection details only):

targets:
  - name: fw1
    platform: opnsense       # opnsense | pfsense
    host: 192.0.2.1
    port: 443
    username: <opnsense-api-key>   # OPNsense API key (unused for pfSense)
    verify_ssl: false        # false for self-signed lab certs
  - name: edge
    platform: pfsense
    host: 192.0.2.2
    verify_ssl: false
    scheme: http             # https (default) | http — for a GUI behind a TLS-terminating proxy

The secret — the OPNsense API secret (paired with the key for HTTP Basic auth) or the pfSense API key — is stored encrypted in ~/.firewall-aiops/secrets.enc (Fernet + scrypt-derived key), never plaintext on disk. Set it with firewall-aiops secret set <target> or the init wizard. The store is unlocked by a master password from FIREWALL_AIOPS_MASTER_PASSWORD (non-interactive/MCP/CI) or an interactive prompt (CLI on a TTY). A legacy plaintext env var FIREWALL_<TARGET>_SECRET is honoured as a fallback (migrate with firewall-aiops secret migrate).

Governance

Every MCP tool is wrapped by @governed_tool:

  • Audit — every call is logged to ~/.firewall-aiops/audit.db (tool, params with secrets redacted, status, duration, risk tier, approver, rationale).
  • Budget / runaway guard — per-process token/call caps and a repeat-call circuit breaker (FIREWALL_MAX_TOOL_CALLS, FIREWALL_RUNAWAY_MAX, …).
  • Risk-tier labelling — each tool's declared risk_level is recorded on its audit row as a descriptive tier (a label, not a gate); there is no read-only switch, policy file, or approval gate. FIREWALL_AUDIT_APPROVED_BY and FIREWALL_AUDIT_RATIONALE are optional audit annotations, recorded when set but never required.
  • Undo recording — reversible writes record an inverse descriptor to ~/.firewall-aiops/undo.db from the fetched before-state (recording only; an external orchestrator executes it).
  • Sanitisation — all firewall-returned text is bounded + injection-sanitised before it reaches the agent.

Platform support & verification status

  • Platforms: OPNsense (REST API) and pfSense (REST API v2, pfSense-pkg-RESTAPI).
  • Test coverage: behaviour is validated against mocked OPNsense/pfSense JSON responses — every module imports, every MCP tool carries the governance marker, the RCA heuristics are unit-tested against synthetic telemetry, and reversible writes are asserted to record the correct inverse undo descriptor. The concrete REST paths are modelled from each project's public API and have not yet been exercised against a live firewall. See docs/VERIFICATION.md for the checklist a live run must satisfy; firewall-aiops doctor (a firmware/version query on both platforms) is the fastest connectivity check. Both platforms are free and self-hostable (OPNsense is fully open-source; pfSense CE is free), so a home lab is the easiest place to run it.
  • Missing a capability? Open an issue or PR at github.com/AIops-tools/Firewall-AIops — contributions and feedback welcome.

License

MIT — see LICENSE.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured