Security Misconfiguration in Fiber with Dynamodb

Security misconfiguration in a Fiber application that interacts with DynamoDB commonly arises from overly permissive IAM policies, unvalidated input used to construct DynamoDB API calls, and missing runtime checks. When these issues align, an attacker may be able to read or modify data that should be isolated between users or perform unintended operations on the table.

For example, if a Fiber route uses path or query parameters directly to build GetItem or Scan inputs without strict allowlists and type checks, an attacker can manipulate the request to target different partition keys or sort keys. A route like /users/:userId/profile that constructs a DynamoDB KeyConditionExpression from req.params.userId without validating format or ownership can enable IDOR-like behavior across users. Similarly, passing raw user input into a FilterExpression or building attribute names dynamically can lead to situations where additional data is returned or operations affect more items than intended.

Misconfigured IAM credentials attached to the runtime environment can further amplify impact. If the credentials grant broader table access than necessary (for example, dynamodb:Scan or dynamodb:Query on a production table), a compromised or vulnerable endpoint can lead to mass data exposure or destructive operations. Another misconfiguration risk is failing to enforce encryption in transit and at rest or relying on default AWS region endpoints without explicit configuration, which can expose data in transit or route requests to unintended regions.

Using middleBrick to scan an unauthenticated Fiber + DynamoDB API surface will often flag these issues under BOLA/IDOR, Input Validation, and Data Exposure checks, highlighting endpoints where user-supplied data reaches DynamoDB calls without adequate constraints. The scanner also checks whether responses inadvertently expose sensitive attributes, indicating that table design or response serialization needs tightening.

Remediation focuses on strict input validation, least-privilege IAM, and defensive coding patterns when constructing DynamoDB requests. Below are concrete, realistic examples for a Fiber route that retrieves a user profile by ID.

First, validate and constrain the incoming identifier. Do not trust path parameters. Use a strict pattern and convert to a known type before using it in DynamoDB calls:

import { Router } from 'express';
import { DynamoDBClient, GetItemCommand } from '@aws-sdk/client-dynamodb';
import { unmarshall } from '@aws-sdk/util-dynamodb';

const router = Router();
const client = new DynamoDBClient({ region: 'us-east-1' });

// Strict validation helper
function isValidUserId(value: string): boolean {
  return /^[a-f0-9-]{36}$/i.test(value); // example UUID pattern
}

router.get('/users/:userId/profile', async (req, res) => {
  const { userId } = req.params;
  if (!isValidUserId(userId)) {
    return res.status(400).json({ error: 'invalid user id' });
  }

  const command = new GetItemCommand({
    TableName: process.env.PROFILE_TABLE_NAME,
    Key: {
      pk: { S: `USER#${userId}` },
      sk: { S: 'PROFILE' }
    },
    // Explicit projection to return only necessary attributes
    ProjectionExpression: 'username,email,updatedAt'
  });

  try {
    const response = await client.send(command);
    if (!response.Item) {
      return res.status(404).json({ error: 'not found' });
    }
    res.json(unmarshall(response.Item));
  } catch (err) {
    console.error(err);
    res.status(500).json({ error: 'internal error' });
  }
});

Second, apply least-privilege IAM. Ensure the runtime role only allows required actions on the specific table and key pattern. Avoid wildcards like dynamodb:* or broad resource ARNs:

# Example IAM policy snippet (do not embed in code; attach to role)
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "dynamodb:GetItem",
        "dynamodb:Query"
      ],
      "Resource": "arn:aws:dynamodb:us-east-1:123456789012:table/Profiles"
    }
  ]
}

Third, avoid dynamic expression building from raw input. If you need advanced queries, use an allowlisted set of fields rather than concatenating user input into FilterExpression or KeyConditionExpression. For scans or queries that require filtering, prefer server-side filtering with explicit expressions:

// Safe: using a fixed expression name and value placeholder
const command = new QueryCommand({
  TableName: process.env.EVENTS_TABLE_NAME,
  IndexName: 'GSI_STATUS',
  KeyConditionExpression: 'status = :statusVal',
  ExpressionAttributeValues: {
    ':statusVal': { S: 'active' }
  },
  FilterExpression: ' begins_with (id, :pkPrefix)',
  ExpressionAttributeNames: {
    '#pk': 'id'
  },
  ExpressionAttributeValues: {
    ':pkPrefix': { S: 'ORDER#' }
  }
});

Finally, enable encryption settings explicitly in client configuration where supported and ensure environment variables like AWS_REGION are set to a known region. Combine these practices with middleBrick scans to continuously verify that runtime behavior aligns with intended security controls.