Brute Force Attack in Loopback with Dynamodb
Brute Force Attack in Loopback with Dynamodb — how this specific combination creates or exposes the vulnerability
A brute force attack against a Loopback application backed by DynamoDB typically targets authentication or password-reset endpoints that rely on a DynamoDB data source. When rate limiting is absent or misconfigured, an attacker can send many credential guesses against a single user or enumerate valid users by observing differences in response behavior. Because Loopback connectors for DynamoDB do not enforce server-side lockout by default, the backend may process each attempt without throttling, allowing rapid, low-cost guesses.
In this setup, DynamoDB itself does not introduce the brute force vector, but it can amplify risk if user data (e.g., usernames, password digests, or password reset tokens) is stored in easily queryable tables without additional protections. An attacker who discovers or guesses a valid username can iterate through password guesses and monitor responses for timing differences or inconsistent error messages, which can confirm valid accounts. If the application uses predictable reset tokens stored in DynamoDB and does not enforce strict token entropy or short lifetimes, token brute force becomes feasible.
Another angle involves unauthenticated endpoints that query DynamoDB based on user-supplied identifiers. For example, an endpoint like /api/users/{id} that reads from a DynamoDB table may reveal whether a given ID exists depending on response content or HTTP status codes. An attacker can brute force numeric or UUID identifiers to map valid resources. Because Loopback’s default scaffolding may expose such routes and DynamoDB permissions might be broadly permissive in development, the combination lowers the bar for enumeration.
During a middleBrick scan, such weaknesses are surfaced through checks for rate limiting, authentication enforcement, and input validation across the 12 security checks. The scanner tests whether the API responds differently to valid versus invalid credentials, whether account lockout or exponential backoff is present, and whether DynamoDB-backed endpoints leak existence information. Findings include severity ratings and remediation guidance, emphasizing defense-in-depth: strong authentication, consistent error handling, and server-side throttling.
Dynamodb-Specific Remediation in Loopback — concrete code fixes
To harden a Loopback application using DynamoDB against brute force, apply server-side controls and consistent patterns. The goal is to make authentication endpoints uniform in response behavior and to enforce throttling regardless of backend storage. The following examples assume you are using the loopback-connector-dynamodb connector.
1. Consistent error responses
Always return the same HTTP status and message shape for authentication failures to prevent user enumeration. Avoid branching logic that reveals whether a username exists.
// common/models/user.json (excerpt)
{
"name": "user",
"base": "User",
"options": {
"validateUpsert": true
},
"properties": {
"username": { "type": "string", "required": true },
"password": { "type": "string", "required": true },
"passwordResetToken": { "type": "string" },
"passwordResetTokenExpiry": { "type": "date" }
}
}
// common/models/user.js
module.exports = function(User) {
User.authenticate = async function(credentials) {
const { username, password } = credentials;
// Fetch user by username from DynamoDB via the Loopback connector
const user = await User.findOne({ where: { username } });
// Use a constant-time comparison in real code; simplified here
const valid = user && user.password === password; // placeholder: use hashed comparison
// Always return the same shape and status to avoid enumeration
if (!valid) {
const err = new Error('Invalid credentials');
err.statusCode = 401;
throw err;
}
return { id: user.id, username: user.username };
};
};
2. Rate limiting and account lockout
Implement rate limiting at the model or global level. You can use a simple in-memory map for prototyping, but prefer a shared store in production. Enforce account lockout or exponential backoff after repeated failures.
// server/middleware.json
{
"initial:before": {
"loopback#rest": {
"params": {
"paths": [".*"],
"log": true
}
}
}
}
// common/models/user.js (continued)
const attempts = new Map(); // replace with Redis or similar in production
User.loginWithThrottle = async function(credentials) {
const { username } = credentials;
const key = `login_failures:${username}`;
const now = Date.now();
const window = 60 * 1000; // 1 minute
const maxAttempts = 5;
// Clean old entries (simplified)
if (attempts.has(key)) {
const { count, last } = attempts.get(key);
if (now - last > window) {
attempts.set(key, { count: 1, last: now });
} else if (count >= maxAttempts) {
const err = new Error('Account temporarily locked');
err.statusCode = 403;
throw err;
} else {
attempts.set(key, { count: count + 1, last: now });
}
} else {
attempts.set(key, { count: 1, last: now });
}
return User.authenticate(credentials);
};
3. Secure DynamoDB access patterns
Ensure queries are parameterized and do not expose internal IDs directly. Use indexed lookups and avoid scanning. For password resets, generate high-entropy tokens with short TTLs and store them securely.
// Example: safe token generation and storage
const crypto = require('crypto');
User.resetPasswordToken = async function(username) {
const token = crypto.randomBytes(32).toString('hex');
const expires = new Date(Date.now() + 15 * 60 * 1000); // 15 minutes
await User.updateOne(
{ where: { username } },
{ passwordResetToken: token, passwordResetTokenExpiry: expires }
);
return token;
};
// Example: verify token with constant-time comparison where feasible
User.verifyResetToken = async function(username, token) {
const user = await User.findOne({ where: { username } });
if (!user) {
// Still perform a dummy operation to keep timing similar
crypto.timingSafeEqual(Buffer.alloc(32), Buffer.from(token));
throw new Error('Invalid token');
}
const valid = crypto.timingSafeEqual(Buffer.from(user.passwordResetToken), Buffer.from(token));
if (!valid || user.passwordResetTokenExpiry < new Date()) {
throw new Error('Invalid or expired token');
}
return user;
};
4. Middleware and global protections
Use Loopback middleware to enforce rate limits and input validation before requests reach DynamoDB connectors. This reduces load and prevents abuse patterns.
// server/component-config.json (excerpt for rate limiting via custom middleware)
{
"components": {
"middleware": {
"initial": {
"bruteForceGuard": {
"action": "loopback#rest",
"config": {
"requestLimit": 100,
"interval": 60000
}
}
}
}
}
}