Broken Authentication in Restify with Dynamodb

Broken Authentication occurs when identity management is implemented incorrectly, allowing attackers to compromise passwords, keys, or session tokens. In a Restify service that uses Amazon DynamoDB as the user store, the combination of an insecure API layer and a misconfigured NoSQL data store can expose authentication flows to enumeration, credential leakage, and token abuse.

Restify is a Node.js server framework commonly used to build APIs. When authentication endpoints (such as /login or /token) are implemented without proper controls, attackers can exploit timing differences, missing rate limits, or verbose error messages. DynamoDB, when used without defensive coding patterns, can unintentionally reveal whether a username exists through differences in response behavior or through conditional writes that do not enforce uniqueness correctly.

For example, an attacker may send two login requests with slightly altered payloads and observe whether response times or status messages differ. If DynamoDB queries use a GetItem or Query without consistent error handling, the application might return a 404-like message for a non-existent user while returning user data for an existing user, enabling username enumeration. This becomes more dangerous when the user identifier is an email address that is also stored in plaintext or with weak encryption, violating data exposure controls.

Additionally, if the authentication logic relies on client-supplied identifiers without re-verifying them against a server-side session store in DynamoDB, it may be vulnerable to IDOR or BOLA (Broken Object Level Authorization). An attacker could modify the user identifier in the request (e.g., changing a UUID in the URL or body) and access another user’s profile or authentication tokens if IAM policies or application-level checks are too permissive.

Real-world patterns that increase risk include using DynamoDB conditional writes that do not enforce uniqueness on usernames or emails, leading to duplicate accounts that bypass authentication checks. Another pattern is storing session tokens in DynamoDB with a Time to Live (TTL) that is either too long or not enforced consistently, enabling session fixation or long-lived hijacked sessions. These issues map directly to OWASP API Top 10 controls, particularly Authentication and Data Exposure, and can be detected by scanning an endpoint with tools capable of comparing spec-defined behavior against runtime responses.

To mitigate Broken Authentication in Restify when using DynamoDB, implement consistent error handling, enforce uniqueness constraints, and avoid leaking information through timing or error messages. Below are code examples that demonstrate secure patterns for user registration and login using the AWS SDK for JavaScript (v3).

First, ensure that user creation uses a conditional write to prevent duplicate usernames or emails. This reduces the risk of account enumeration and enforces a single identity per user.

const { DynamoDBClient, PutItemCommand } = require("@aws-sdk/client-dynamodb");
const client = new DynamoDBClient({ region: "us-east-1" });

async function createUser(username, email, passwordHash) {
  const params = {
    TableName: "Users",
    Item: {
      username: { S: username },
      email: { S: email },
      passwordHash: { S: passwordHash },
      createdAt: { S: new Date().toISOString() }
    },
    ConditionExpression: "attribute_not_exists(username) AND attribute_not_exists(email)"
  };
  try {
    await client.send(new PutItemCommand(params));
    return { success: true };
  } catch (err) {
    if (err.name === "ConditionalCheckFailedException") {
      return { success: false, reason: "username_or_email_exists" };
    }
    throw err;
  }
}

Second, during login, use a GetItem query with a consistent response path and timing. Always perform a dummy computation and return the same status code and generic message regardless of whether the user exists, to prevent timing and enumeration attacks.

const { DynamoDBClient, GetItemCommand } = require("@aws-sdk/client-dynamodb");
const client = new DynamoDBClient({ region: "us-east-1" });

async function getUserByUsername(username) {
  const params = {
    TableName: "Users",
    Key: {
      username: { S: username }
    }
  };
  const result = await client.send(new GetItemCommand(params));
  return result.Item || null;
}

async function authenticate(username, passwordHash) {
  const user = await getUserByUsername(username);
  // Perform constant-time comparison in application layer
  const isValid = user && user.passwordHash?.S === passwordHash;
  // Always return same response shape to avoid leaking existence
  return {
    authenticated: isValid,
    token: isValid ? "session-token-here" : null
  };
}

Third, store session tokens in DynamoDB with a TTL attribute and validate them on each request. Ensure that token lookup does not reveal whether a token is valid by returning opaque errors when authorization fails.

const { DynamoDBClient, UpdateItemCommand, GetItemCommand } = require("@aws-sdk/client-dynamodb");
const client = new DynamoDBClient({ region: "us-east-1" });

async function revokeToken(tokenId) {
  const params = {
    TableName: "Sessions",
    Key: { tokenId: { S: tokenId } },
    UpdateExpression: "SET revoked = :r",
    ExpressionAttributeValues: { ":r": { BOOL: true } }
  };
  await client.send(new UpdateItemCommand(params));
}

async function getSession(tokenId) {
  const params = {
    TableName: "Sessions",
    Key: { tokenId: { S: tokenId } },
    ProjectionExpression: "userId, expiresAt, revoked"
  };
  const result = await client.send(new GetItemCommand(params));
  return result.Item || null;
}

Finally, integrate these checks into your Restify routes with uniform error handling and rate limiting. The Pro plan of middleBrick includes continuous monitoring and can be added to CI/CD pipelines via the GitHub Action to fail builds if insecure patterns are detected in your API definitions. The CLI tool allows you to scan from the terminal with middlebrick scan <url>, while the MCP Server enables scanning directly from AI coding assistants in your IDE.