Format String in Dynamodb

Format string vulnerabilities in DynamoDB contexts typically arise when user input is directly interpolated into DynamoDB expressions without proper sanitization. While DynamoDB's Query and Scan operations don't use traditional printf-style format strings, the concept manifests through unsafe expression construction.

The most common DynamoDB format string issues occur in:

• KeyConditionExpression where partition keys or sort keys are dynamically constructed
• FilterExpression where filter criteria are built from user input
• UpdateExpression where attribute names or values are dynamically inserted
• ProjectionExpression where attribute lists are constructed

Consider this vulnerable pattern:

const userId = req.query.userId; // User input
const params = {
  TableName: 'Users',
  KeyConditionExpression: 'userId = :id',
  ExpressionAttributeValues: {
    ':id': userId
  }
};
const result = await dynamodb.query(params).promise();

This appears safe at first glance, but if userId contains special characters or malicious expressions, it could manipulate the query logic. More dangerous is when developers attempt to dynamically construct attribute names:

const attribute = req.query.attribute; // User-controlled
const value = req.query.value; // User-controlled
const params = {
  TableName: 'Products',
  FilterExpression: `${attribute} = :val`,
  ExpressionAttributeValues: {
    ':val': value
  }
};
const result = await dynamodb.scan(params).promise();

Here, an attacker could supply attribute names that modify the query structure or inject unintended conditions.

Another DynamoDB-specific manifestation involves partition key injection:

const pk = req.query.pk; // User input
const params = {
  TableName: 'Orders',
  KeyConditionExpression: 'PK = :pk AND begins_with(SK, :sk)',
  ExpressionAttributeValues: {
    ':pk': pk,
    ':sk': 'ORDER#'
  }
};
const result = await dynamodb.query(params).promise();

If pk contains special characters or expressions, it could alter the query's logical flow or access unintended data.

Detecting format string vulnerabilities in DynamoDB requires analyzing how expressions are constructed and validated. Static analysis tools can identify dangerous patterns, but runtime scanning provides the most accurate detection.

middleBrick's DynamoDB scanning specifically looks for:

• Dynamic expression construction where user input influences KeyConditionExpression, FilterExpression, or UpdateExpression
• Missing ExpressionAttributeNames usage when attribute names are dynamic
• Unsafe interpolation of user data into DynamoDB parameters
• Missing validation of partition and sort key values

Runtime detection involves sending crafted payloads to test for injection vulnerabilities:

// Test for KeyConditionExpression injection
const maliciousPk = 'USER#123 OR begins_with(SK, :sk)';
const params = {
  TableName: 'Users',
  KeyConditionExpression: 'PK = :pk AND begins_with(SK, :sk)',
  ExpressionAttributeValues: {
    ':pk': maliciousPk,
    ':sk': 'ORDER#'
  }
};
const result = await dynamodb.query(params).promise();
// If this returns unexpected results, injection is possible

middleBrick automates this testing by:

• Analyzing the API's DynamoDB usage patterns from OpenAPI specifications
• Crafting boundary test cases for each expression parameter
• Testing for injection through special characters and boolean operators
• Verifying proper use of ExpressionAttributeNames and ExpressionAttributeValues

The scanner also checks for common DynamoDB anti-patterns:

middleBrick's continuous monitoring can detect when DynamoDB configurations change and automatically re-scan for format string vulnerabilities in the updated code paths.

Remediating format string vulnerabilities in DynamoDB requires a defense-in-depth approach using the service's built-in security features and proper input validation.

1. Use ExpressionAttributeNames for Dynamic Attributes

Instead of interpolating attribute names directly, use ExpressionAttributeNames to safely reference dynamic attributes:

const attribute = req.query.attribute;
const value = req.query.value;

// Validate attribute against whitelist
const validAttributes = ['username', 'email', 'status'];
if (!validAttributes.includes(attribute)) {
  throw new Error('Invalid attribute');
}

const params = {
  TableName: 'Users',
  FilterExpression: '#attr = :val',
  ExpressionAttributeNames: {
    '#attr': attribute
  },
  ExpressionAttributeValues: {
    ':val': value
  }
};
const result = await dynamodb.scan(params).promise();

2. Strict Input Validation

Implement strict validation for partition and sort keys:

function validatePartitionKey(pk) {
  // Enforce strict pattern for partition keys
  const pkPattern = /^USER#\d+$/; // Example: USER#12345
  if (!pkPattern.test(pk)) {
    throw new Error('Invalid partition key format');
  }
  return pk;
}

function validateSortKey(sk) {
  // Validate sort key format based on your schema
  const skPattern = /^(ORDER#\d+|PROFILE#\d+)$/;
  if (!skPattern.test(sk)) {
    throw new Error('Invalid sort key format');
  }
  return sk;
}

// Usage
const userId = validatePartitionKey(req.query.userId);
const orderId = validateSortKey(req.query.orderId);

const params = {
  TableName: 'Orders',
  KeyConditionExpression: 'PK = :pk AND SK = :sk',
  ExpressionAttributeValues: {
    ':pk': userId,
    ':sk': orderId
  }
};
const result = await dynamodb.query(params).promise();

3. Use Parameterized Queries

Always use ExpressionAttributeValues instead of direct interpolation:

// Vulnerable
const params = {
  TableName: 'Users',
  KeyConditionExpression: 'username = ' + username
};

// Secure
const params = {
  TableName: 'Users',
  KeyConditionExpression: 'username = :username',
  ExpressionAttributeValues: {
    ':username': username
  }
};

4. Implement Least Privilege

Configure IAM policies with the principle of least privilege:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "dynamodb:GetItem",
        "dynamodb:Query",
        "dynamodb:Scan"
      ],
      "Resource": "arn:aws:dynamodb:region:account-id:table/Users"
    }
  ]
}

5. Use middleBrick for Continuous Security

Integrate middleBrick into your development workflow to catch format string vulnerabilities early:

# Scan your API endpoints
middlebrick scan https://api.example.com/users

# Add to CI/CD with GitHub Action
- name: middleBrick Security Scan
  uses: middlebrick/middlebrick-action@v1
  with:
    api-url: 'https://api.example.com'
    fail-on-severity: 'high'
    scan-type: 'dynamodb'

middleBrick's DynamoDB-specific scanning provides detailed findings with severity levels and remediation guidance, helping you maintain secure DynamoDB implementations throughout your development lifecycle.