Cache Poisoning in Sails with Cockroachdb

Cache poisoning in a Sails application backed by CockroachDB occurs when an attacker causes the application or an intermediate cache to store malicious or incorrect data that is later served to other users or used in security-sensitive decisions. In this stack, Sails typically interacts with CockroachDB as a distributed SQL datastore. If Sails caches query results, model instances, or computed values without strict validation and isolation, poisoned entries can survive cache eviction and affect subsequent requests.

Several conditions specific to this combination increase exposure:

• Dynamic model associations and Waterline ORM queries can produce complex joins across distributed SQL nodes. If a cached result includes user-controlled fields used to construct subsequent queries, an attacker may inject values that change the meaning of the cached dataset.
• CockroachDB’s strong consistency and serializable isolation help avoid stale reads within a transaction, but if Sails caches data at the application layer and then reuses it across transactions or with different tenants, the cache can become a vector for privilege escalation or information leakage.
• Unauthenticated endpoints or overly permissive model policies in Sails may allow an unauthenticated attacker to cause the server to cache attacker-controlled content. For example, an endpoint that accepts an identifier and caches the resulting record set without validating tenant context can cause one user’s data to be served to another user (a BOLA/IDOR pattern facilitated by cached data).
• Cache poisoning can also arise from query parameters that influence caching keys. If Sails builds cache keys from unescaped user input and stores them alongside sensitive metadata, an attacker may craft keys that collide with legitimate entries or overwrite important cached configuration.

Real-world parallels to this risk appear in the OWASP API Top 10 category ‘Broken Object Level Authorization’ and in general data exposure scenarios where incorrect data is returned due to corrupted cache state. Although CockroachDB itself does not introduce the poisoning, the distributed nature of the database can make cache invalidation across nodes more complex, increasing the chance that stale or malicious data persists.

An example attack chain:

1. An unauthenticated endpoint in Sails accepts a collectionId parameter and caches the list of items.
2. An attacker sends a request with a malicious collectionId that causes the server to cache a dataset they can influence.
3. Subsequent legitimate users request the same endpoint with a different collectionId, but due to a cache key collision or lack of tenant isolation they receive the attacker’s cached data, leading to information disclosure or logic bypass.

Because middleBrick performs black-box scans testing unauthenticated attack surfaces, it can flag endpoints that cache data without proper authorization checks, input validation, or tenant separation, mapping findings to relevant controls in frameworks such as OWASP API Top 10 and GDPR.

Remediation focuses on strict input validation, tenant-aware caching, and safe query construction. Avoid using raw user input in cache keys, and ensure cached entries are scoped by tenant and validated before reuse. Below are concrete practices and code examples for Sails with CockroachDB.

1. Validate and sanitize inputs before using them in queries or cache keys

Ensure that parameters such as IDs and collection selectors are strictly typed and checked against a known allowlist or format. Use Sails’ built-in validation and sanitizers.

// api/controllers/ItemController.js
'use strict';
const { isUUID, isInt } = require('validator');

module.exports = {
  listItems: async function (req, res) {
    const { collectionId, userId } = req.allParams();

    // Strict validation
    if (!isUUID(collectionId, 4)) {
      return res.badRequest('Invalid collection identifier');
    }
    if (!isUUID(userId, 4)) {
      return res.badRequest('Invalid user identifier');
    }

    // Proceed with a parameterized query
    const items = await Item.find({
      where: {
        collectionId: collectionId,
        userId: userId,
      },
    });

    return res.ok(items);
  },
};

2. Scope cache keys with tenant and ownership information

Include tenant or user context in cache keys to prevent cross-tenant leaks. If using an external cache, ensure keys incorporate the tenant ID or user ID.

// api/services/cacheService.js
'use strict';
const crypto = require('crypto');

/**
 * Build a deterministic, tenant-aware cache key.
 * @param {string} base - A descriptive base, e.g., 'items:list'
 * @param {object} params - An object of parameters that affect the result
 * @param {string} tenantId - The tenant or user UUID
 * @returns {string}
 */
function buildCacheKey(base, params, tenantId) {
  const normalized = Object.keys(params)
    .sort()
    .map((k) => `${k}:${params[k]}`)
    .join('|');
  const hash = crypto.createHash('sha256').update(`${tenantId}|${base}|${normalized}`).digest('hex');
  return `v1:${hash}`;
}

module.exports = { buildCacheKey };

3. Use CockroachDB parameterized queries to avoid injection and ensure correct typing

When using an ORM or query builder, prefer parameterized APIs. If you drop to raw queries, use placeholders consistently.

// api/models/Item.js
'use strict';

module.exports = {
  attributes: {
    name: 'string',
    collectionId: 'string',
    userId: 'string',
    metadata: 'json',
  },
};

// Example raw query using node-postgres with CockroachDB
// In a custom service, prefer Waterline or an ORM that enforces parameterization
const pool = require('pg').Pool; // hypothetical wrapper
const db = new pool({
  connectionString: process.env.DATABASE_URL,
});

async function fetchItemsForCollection(collectionId, userId) {
  const client = await db.connect();
  try {
    const result = await client.query(
      'SELECT id, name, metadata FROM items WHERE collection_id = $1 AND user_id = $2',
      [collectionId, userId]
    );
    return result.rows;
  } finally {
    client.release();
  }
}

module.exports = { fetchItemsForCollection };

4. Implement cache invalidation tied to data ownership and access control

When data changes, invalidate only the affected tenant-scoped cache entries. Do not use global keys that span tenants.

// api/services/cacheInvalidation.js
'use strict';
const { buildCacheKey } = require('./cacheService');

async function invalidateCollectionCache({ collectionId, tenantId }) {
  const key = buildCacheKey('items:list', { collectionId }, tenantId);
  // Use your cache provider’s delete API, e.g., Redis DEL
  await cache.del(key);
}

module.exports = { invalidateCollectionCache };

5. Enforce authorization on every read, even when serving cached data

Never serve cached data without re-checking ownership or permissions. Use policies that align with the data access patterns of Sails models.

// api/policies/tenantOwnership.js
'use strict';

module.exports = async function (req, res, proceed) {
  const { id } = req.params;
  const userId = req.session.userId;

  if (!id || !userId) {
    return res.forbidden('Missing identifiers');
  }

  // Ensure the requested item belongs to the user’s tenant
  const item = await Item.findOne(id);
  if (!item || item.userId !== userId) {
    return res.forbidden('Not authorized');
  }

  return proceed();
};

By combining strict input validation, tenant-aware cache keys, parameterized database access, and per-request authorization, the risk of cache poisoning in a Sails + CockroachDB deployment is substantially reduced. These practices align with findings that middleBrick may surface, such as improper authorization and input validation, and support remediation guidance tied to compliance frameworks like OWASP API Top 10 and SOC2.