Api Rate Abuse in Sails with Cockroachdb

Rate abuse in a Sails application backed by CockroachDB arises from a mismatch between API request volume and backend query handling. Sails, being a Node.js MVC framework, typically handles requests asynchronously; if routes or controllers issue frequent or unbounded queries to CockroachDB without throttling or validation, an attacker can send many rapid requests that generate heavy SQL execution and connection pressure. CockroachDB, while horizontally scalable, still experiences load from each SQL transaction, and poorly constrained queries can consume significant compute and I/O. This combination exposes endpoints to enumeration, brute-force, or resource exhaustion when rate controls are absent or misconfigured.

Specific vulnerability patterns include missing per-identity or per-IP limits on authentication endpoints (e.g., /login or /auth/local), unthrottled search or lookup routes that perform full-table scans or index-heavy queries in CockroachDB, and absence of concurrency caps on actions that trigger multiple database transactions. Without rate limiting, an attacker can automate credential stuffing or API key probing, leveraging CockroachDB’s consistent latency to iterate quickly. Sails’ policy/controller architecture can inadvertently allow these bursts if before-action hooks or model methods do not enforce request budgeting or if custom logic does not integrate with shared-rate stores (e.g., Redis-backed counters). The risk is amplified when routes expose primary keys or predictable identifiers, enabling low-cost, high-volume queries that stress CockroachDB nodes and degrade availability for legitimate users.

Additionally, Sails Waterline ORM can generate suboptimal SQL under complex associations or populate directives, increasing per-request load on CockroachDB when endpoints return large nested datasets. If bulk endpoints lack pagination or query cost analysis, an attacker can craft requests that trigger heavy JOINs or aggregations, magnifying resource consumption. Misconfigured database indexes in CockroachDB can further exacerbate the impact by causing full-range scans. Therefore, securing this stack requires coordinated controls: explicit rate policies, efficient query design, and observability to detect abnormal patterns before they affect stability.

Implement rate limiting at the Sails layer using a shared store such as Redis to coordinate request counts across instances. For CockroachDB, optimize queries with targeted indexes and bounded result sets, and ensure Waterline usage avoids expensive operations. Below are concrete code examples tailored to this stack.

• Rate-limiting policy using Redis in Sails (config/policies.js):

// config/policies.js
module.exports.policies = {
  '*': ['rateLimiter'],
  AuthController: { login: ['rateLimiter', 'authenticate'] },
  UserController: { search: ['rateLimiter', 'find'] }
};

// api/hooks/rateLimiter/index.js
const Redis = require('ioredis');
const client = new Redis({ host: '127.0.0.1' });
module.exports = async function rateLimiter(req, res, next) {
  const key = req.ip + ':' + req.route.path;
  const limit = 60; // requests
  const window = 60; // seconds
  const current = await client.incr(key);
  if (current === 1) await client.expire(key, window);
  if (current > limit) return res.status(429).json({ error: 'Rate limit exceeded' });
  return next();
};

• CockroachDB-specific query optimization in Sails models (api/models/User.js):

// api/models/User.js
module.exports = {
  attributes: {
    email: { type: 'string', required: true, unique: true },
    role: { type: 'string', defaultsTo: 'user' },
    // Ensure an index on email for fast lookups
  },
  beforeCreate: async function (values, proceed) {
    // Use parameterized queries to avoid injection and ensure plan reuse
    const existing = await User.query(
      `SELECT id FROM users WHERE email = $1 LIMIT 1`,
      [values.email]
    );
    if (existing.length) return proceed('Email already registered');
    return proceed();
  }
};

• Waterline query with pagination and bounded fields to reduce CockroachDB load (api/controllers/UserController.js):

// api/controllers/UserController.js
module.exports = {
  search: async function (req, res) {
    const page = parseInt(req.query.page) || 1;
    const limit = parseInt(req.query.limit) || 20;
    const skip = (page - 1) * limit;
    // Use select to restrict fields and avoid heavy population
    const results = await User.find()
      .where({ status: 'active' })
      .limit(limit)
      .skip(skip)
      .select(['id', 'email', 'role']);
    const total = await User.count().where({ status: 'active' });
    return res.json({ data: results, meta: { page, limit, total } });
  }
};

• CockroachDB session and index guidance (run in CockroachDB SQL shell):

-- Create an index to support efficient email lookups
CREATE INDEX idx_users_email ON users (email);
-- Use bounded transactions to avoid long-running scans
SET max_sql_txn_restart_count = 5;

Together, these steps reduce per-request database pressure and constrain abusive patterns while preserving functionality. Combine with monitoring of query latency and error rates in CockroachDB to refine limits and indexes over time.