Rails Security Multitenancy logo

Rails Security Multitenancy

Community
marckohlbrugge
rails-security-multitenancy

Apply Rails security and multi-tenant safety practices including scoped queries, SSRF defenses, rate limiting, and tenant-scoped realtime updates. Use when implementing auth, webhooks, tenant boundaries, or security-sensitive endpoints.

Overview

Publishermarckohlbrugge
Repository37signals-skills
Skill namerails-security-multitenancy
Stars
724
Forks
56
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by marckohlbrugge on GitHub. Read the source before you install it.

Installation

Install the Rails Security Multitenancy AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/marckohlbrugge/37signals-skills/tree/main/skills/rails-security-multitenancy
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/marckohlbrugge/37signals-skills.git /tmp/37signals-skills
mkdir -p .claude/skills
cp -r /tmp/37signals-skills/skills/rails-security-multitenancy .claude/skills/rails-security-multitenancy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rails Security Multitenancy in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Rails Security Multitenancy on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Rails Security Multitenancy is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Rails Security + Multi-Tenancy

Use for security-sensitive Rails work and tenant-boundary reviews. Patterns from Fizzy (path-based multi-tenant SaaS) and Campfire (single-tenant, bot APIs).

Core Rules

  • Scope all tenant data access through tenant/user ownership boundaries.
  • Never trust naked Model.find(params[:id]) in tenant-aware flows.
  • Scope realtime broadcasts and stream names by tenant/account.
  • Rate-limit auth and abuse-prone endpoints.
  • Treat user-provided URLs as untrusted input.
  • Fail closed (head :forbidden) when access cannot be proven.

Tenancy Architecture (path-based, Fizzy-style)

  • Middleware extracts the account prefix from PATH_INFO into SCRIPT_NAME, loads the account, and wraps the request in Current.with_account(account). URL helpers stay tenant-correct automatically (including ActiveStorage and webhook payload URLs via script_name:).
  • Three-layer auth: Identity → Session → account-scoped User. Sessions attach to an Identity; each request resolves Current.user = identity.users.find_by(account: Current.account). A valid session in account A can never act in account B. Apply the same resolution in ActionCable Connection#connect.
  • Current setters cascade: assigning session resolves identity, assigning identity resolves user for the current account.
  • Auth routes (login, signup, magic links) explicitly opt out of tenancy (disallow_account_scope) and redirect away from tenant-prefixed URLs.
  • Path-scope session cookies (path: account.slug) when simultaneous multi-tenant login is supported.
  • Recurring jobs run outside request context: iterate tenants explicitly (with_each_tenant). Serialize Current.account into job payloads (see rails-jobs).
  • Test the tenancy middleware in isolation with Rack::MockRequest; integration tests set default_url_options[:script_name] from the fixture account.

Scoped Lookups (defense in depth)

Params choose which record within an already-authorized set — never establish access:

ruby
@card = Current.user.accessible_cards.find_by!(number: params[:card_id])   # access graph
@membership = Current.user.memberships.find_by!(room_id: params[:room_id]) # join model
@user = Current.account.users.find(params[:user_id])                       # tenant association
  • Even single-tenant code scopes through associations; wrong IDs 404 naturally.
  • Public sharing uses opaque tokens (has_secure_token :key on a Publication record), never internal IDs.
  • ActiveStorage: attach blobs to accounts, and authorize blob/representation controllers through the domain (blob → attachment → record.accessible_to?(user)); published content gets an explicit publicly_accessible? path.
  • Revoking access cleans up derived data (mentions, notifications, watches) via a scoped async job — don't leave dangling cross-boundary state.

Authentication Hardening

  • Magic links / codes: single-use (consume destroys the row), short-lived, compared with secure_compare, bound to the email via a verified pending-auth cookie.
  • Anti-enumeration: unknown email gets the same fake flow/UX as a real one.
  • API tokens: HTTP-method-scoped permissions (read-only tokens can't POST); show generated secrets once via a short-lived message verifier (~10s), then never again.
  • Bot/automation auth as an explicit mode: skip CSRF only for bot-key auth, deny bots everywhere by default (deny_bots + allow_bot_access only:).
  • Rate limit with Rails built-ins, with responses matching endpoint semantics:
ruby
rate_limit to: 10, within: 15.minutes, only: :create,
  with: -> { redirect_to ..., alert: "Try again in 15 minutes." }
  • Throttle session bookkeeping writes (update last_active_at at most hourly).
  • Filter sensitive params beyond passwords: message bodies, push endpoints, tokens.

SSRF Defense Baseline

For webhooks, push endpoints, unfurling — any user-influenced URL:

  • Resolve DNS and validate the destination IP before the request; block loopback/private/link-local/IPv4-mapped-IPv6 ranges (link-local = cloud metadata).
  • Pin the request to the validated IP (Net::HTTP.new(host, port, ipaddr: resolved_ip)) to beat DNS rebinding.
  • Validate at creation time and again at execution time.
  • Re-resolve and re-validate on every redirect hop — redirect chains are the classic bypass.
  • Cap response sizes (content-length pre-check + chunked read limit) to prevent memory DoS.
  • Layer allowlists on top where the destination set is known (web push: permitted vendor host suffixes AND public-IP resolution).

CSRF and Caching

  • Never HTTP-cache pages that render forms/CSRF tokens.
  • Add Sec-Fetch-Site verification (same-origin/same-site) on top of origin checks; roll out in report-only mode first, and append Sec-Fetch-Site to the Vary header.
  • Set a CSP with a hard floor (object_src :none, base_uri :none, frame_ancestors :self); use report-only + report_uri to validate before enforcing.
  • Private apps: send X-Robots-Tag: none.

Authorization Defaults

  • Predicate methods on models (card.editable_by?(user), user.can_administer_board?(board)); controllers check and head :forbidden.
  • Declarative controller macros (allow_unauthenticated_access, ensure_can_administer) over scattered conditionals.
  • Centralize shared guard logic in small concerns.

Abuse Response

  • Banning a user cascades: convert their session IPs to bans, disconnect ActionCable remotely, delete sessions, purge content async with UI broadcasts.
  • Enforce IP bans only on mutating requests (POST/PUT/PATCH/DELETE).
  • Validate ban targets are public IPs — never let loopback/private ranges be banned.
  • Disconnect deactivated users: ActionCable.server.remote_connections.where(current_user: user).disconnect(reconnect: false).

Inbound Webhooks (receiving)

  • Verify signatures (e.g. Stripe::Webhook.construct_event), then re-fetch canonical state from the source API rather than trusting payload contents/ordering.

Red Flags

  • Tenant-unscoped broadcast channels or stream names.
  • Tenant data inferred from request params without ownership checks.
  • A global User looked up by session without account scoping (identity/user conflation).
  • Webhook or fetch requests to unvalidated destinations; redirects followed without re-validation.
  • ActiveStorage URLs that bypass domain authorization.
  • Security controls hidden in ad-hoc conditionals across controllers.
  • Secrets permanently visible in admin UIs.
  • Auth endpoints without rate limiting.

Frequently asked questions

What does the Rails Security Multitenancy AI skill do?

Apply Rails security and multi-tenant safety practices including scoped queries, SSRF defenses, rate limiting, and tenant-scoped realtime updates. Use when implementing auth, webhooks, tenant boundaries, or security-sensitive endpoints.

Why use Rails Security Multitenancy on TypingMind?

Because you install it once and use it with any model. Rails Security Multitenancy is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Rails Security Multitenancy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/marckohlbrugge/37signals-skills/tree/main/skills/rails-security-multitenancy. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Rails Security Multitenancy?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Rails Security Multitenancy?

As many as you like. As long as a model supports skills, you can use Rails Security Multitenancy with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Rails Security Multitenancy AI skill free?

It is published on GitHub by marckohlbrugge. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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