Injection Flaws in Sails with Cockroachdb

Injection flaws occur when untrusted data is sent to an interpreter as part of a command or query. In Sails.js applications using CockroachDB, the risk centers on how queries are built and executed. CockroachDB uses a PostgreSQL-wire compatible protocol, and many Sails adapters ultimately construct SQL-like statements or pass user input directly into query methods. If inputs are not strictly validated, parameterized, or escaped, attackers can inject malicious payloads that alter query logic.

Consider a typical Sails model query that concatenates user input into a raw SQL fragment:

const search = req.query.q;
const results = await sails.sendNativeQuery('SELECT * FROM accounts WHERE name = \'${search}\';');

Here, the developer embeds search directly into the SQL string. An attacker can provide ' OR '1'='1 to bypass intended filters. Because CockroachDB is compatible with PostgreSQL protocols, attackers may also probe for differences in error messages or behavior compared to other databases to refine injection techniques. Sails Waterline ORM does provide some protection by using parameterized queries when you use its built-in methods, but developers who drop down to native queries or use the query` tag with template literals expose the application.

Another vector arises from dynamic model attribute assignment. Sails allows updates via Model.update with user-provided keys. If keys or values are not strictly validated, injection can manifest as unintended field updates or condition manipulation:

await Account.update({ id: req.params.id }, req.body);

If req.body contains fields like isAdmin or crafted conditionals, an attacker can escalate privileges. Injection flaws in this context are not always about SQL; they can also involve command injection if the application passes user data to external processes, though Sails typically interacts with databases. The unauthenticated attack surface increases when endpoints do not enforce strict schema validation, making middleBrick’s checks for input validation and property authorization particularly valuable for identifying these patterns.

LLM/AI Security is relevant when APIs expose endpoints that generate or manipulate prompts for language models based on user input. If injection flaws exist in prompt assembly—such as directly concatenating user messages into system prompts—attackers can perform prompt injection or jailbreak attempts. middleBrick’s LLM/AI Security checks specifically test for these risks by probing for system prompt leakage and unsafe consumption patterns, which is especially important if your API routes user data into LLM endpoints.

Remediation focuses on using parameterized queries, strict input validation, and avoiding dynamic SQL construction. With CockroachDB and Sails, always prefer Waterline methods that generate parameterized statements, or if using native queries, use placeholders and pass parameters separately.

Instead of string interpolation, use named or positional placeholders. In the native query API supported by most Sails adapters for CockroachDB, supply parameters as a separate array or object:

const search = req.query.q;
const results = await sails.sendNativeQuery('SELECT * FROM accounts WHERE name = $1;', [search]);

This ensures the input is treated strictly as a value, not executable SQL. For more complex conditions, pass an object and reference keys safely:

const filters = { status: 'active', limit: 10 };
const results = await sails.sendNativeQuery(
  'SELECT * FROM accounts WHERE status = $status LIMIT $limit;',
  { status: filters.status, limit: filters.limit }
);

When using Waterline, leverage its built-in methods to avoid raw SQL entirely:

const accounts = await Account.find({ name: req.query.q, limit: 10 });

Waterline translates these into parameterized operations appropriate for CockroachDB. If you must update with dynamic fields, validate and sanitize each key. For instance, use a denylist or allowlist to restrict which fields can be modified:

const safeData = _.pick(req.body, ['email', 'profile']); // allowlist
await Account.updateOne({ id: req.params.id }).set(safeData);

Input validation should be enforced at the controller level. Use libraries compatible with Sails to validate types, lengths, and formats before data reaches the database:

if (!_.isString(req.query.q) || req.query.q.length > 200) {
  return res.badRequest('Invalid query parameter');
}

These practices reduce the attack surface and align with OWASP API Top 10 injection protections. middleBrick’s scans can verify that your endpoints adhere to these patterns, and its GitHub Action can enforce checks in CI/CD pipelines, failing builds if risky query constructions are detected.

For teams using the Pro plan, continuous monitoring can alert you to new endpoints or changes that introduce injection-prone patterns, ensuring ongoing compliance with security frameworks. The MCP Server also allows you to scan APIs directly from your AI coding assistant, helping catch unsafe patterns during development rather than in post-deployment scans.