Broken Access Control in Dynamodb

Broken Access Control in Dynamodb often stems from improper resource access patterns and inadequate authorization checks. Unlike traditional relational databases where you might join user tables with permission tables, Dynamodb's key-value structure and access patterns create unique vulnerabilities.

The most common manifestation is BOLA (Broken Object Level Authorization) through predictable primary keys. Consider this vulnerable pattern:

const params = {
  TableName: 'Users',
  Key: { id: userId }
};

dynamodb.get(params, (err, data) => {
  // No verification that userId belongs to current user
  res.json(data.Item);
});

An attacker can simply increment or modify the userId parameter to access other users' data. This becomes especially dangerous when combined with Dynamodb's scan operations, which can enumerate entire tables if IAM permissions are overly permissive.

Another frequent issue is partition key manipulation. Developers sometimes use predictable partition keys like email addresses or usernames, making it trivial to enumerate valid accounts:

// Vulnerable: predictable partition keys
const params = {
  TableName: 'Users',
  Key: { email: req.query.email }
};

Rate limiting bypasses represent another unique Dynamodb vulnerability. Since Dynamodb charges based on read/write capacity units, developers might implement naive rate limiting that can be circumvented by using different partition keys or attributes.

Cross-account data exposure occurs when developers use the same table for multiple tenants without proper isolation. A common anti-pattern:

// Vulnerable: no tenant isolation
const params = {
  TableName: 'Orders',
  Key: { orderId: req.params.id }
};

Without verifying the tenant ID matches the authenticated user's tenant, any user can access any order by knowing the orderId.

Detecting Broken Access Control in Dynamodb requires both static analysis of code patterns and dynamic testing of API endpoints. middleBrick's scanning engine specifically targets Dynamodb vulnerabilities through several mechanisms.

For static detection, middleBrick analyzes your API endpoints for common Dynamodb anti-patterns. The scanner looks for:

Dynamic testing involves active probing of your API endpoints. middleBrick attempts to access resources using modified identifiers to test for IDOR vulnerabilities. For example, if your endpoint is /api/users/{id}, the scanner will:

1. Access the endpoint with a valid ID to establish baseline
2. Modify the ID parameter systematically (increment, decrement, common values)
3. Check if modified requests return different user data
4. Verify if error messages reveal valid resource existence

middleBrick also tests for partition key enumeration by attempting to access resources with common partition key values like 'admin', 'root', '[email protected]' to identify privilege escalation opportunities.

The scanner specifically checks for Dynamodb's ConditionExpression usage patterns. Missing or improperly implemented condition expressions often indicate authorization bypasses:

// middleBrick flags this as vulnerable
const params = {
  TableName: 'Users',
  Key: { id: userId },
  ConditionExpression: 'attribute_exists(id)'
};

While this condition checks existence, it doesn't verify ownership or tenant isolation.

Fixing Broken Access Control in Dynamodb requires a defense-in-depth approach using the platform's native features. The most effective strategy combines IAM policies, condition expressions, and application-level authorization.

Start with IAM policy hardening. Instead of granting broad dynamodb:* permissions, use resource-level policies with conditions:

const params = {
  TableName: 'Users',
  Key: { id: userId },
  ConditionExpression: 'id = :userId',
  ExpressionAttributeValues: {
    ':userId': userId
  }
};

This condition ensures the partition key matches the authenticated user's ID, preventing access to other users' items even if an attacker knows the key structure.

For multi-tenant applications, implement tenant isolation using composite keys:

// Secure: tenant-scoped composite key
const params = {
  TableName: 'Orders',
  Key: {
    tenantId: req.user.tenantId,
    orderId: req.params.orderId
  },
  ConditionExpression: 'tenantId = :tenantId',
  ExpressionAttributeValues: {
    ':tenantId': req.user.tenantId
  }
};

This pattern ensures that even if someone knows another tenant's orderId, they cannot access it without the correct tenantId.

Implement proper authorization checks before database operations:

async function getUser(userId) {
  // Verify ownership before database call
  if (userId !== req.user.id) {
    throw new Error('Access denied');
  }

  const params = {
    TableName: 'Users',
    Key: { id: userId }
  };

  return dynamodb.get(params).promise();
}

For complex authorization scenarios, use Dynamodb's FilterExpression with Scan operations, but be aware of read capacity costs:

// Secure: filtered scan with authorization
const params = {
  TableName: 'Orders',
  FilterExpression: 'customerId = :customerId',
  ExpressionAttributeValues: {
    ':customerId': req.user.id
  }
};

Consider using Dynamodb's Global Secondary Indexes (GSIs) for efficient tenant-scoped queries without full table scans:

// Create GSI with tenantId as partition key
const createGSI = {
  TableName: 'Orders',
  AttributeDefinitions: [
    { AttributeName: 'tenantId', AttributeType: 'S' },
    { AttributeName: 'orderId', AttributeType: 'S' }
  ],
  GlobalSecondaryIndexUpdates: [{
    Create: {
      IndexName: 'TenantIndex',
      KeySchema: [
        { AttributeName: 'tenantId', KeyType: 'HASH' },
        { AttributeName: 'orderId', KeyType: 'RANGE' }
      ],
      Projection: { ProjectionType: 'ALL' }
    }
  }]
};

Finally, implement comprehensive logging and monitoring to detect anomalous access patterns that might indicate broken access control exploitation attempts.