Email Injection in Dynamodb

Email injection in DynamoDB contexts typically occurs when user-supplied email addresses or related data are improperly validated before being stored or processed. This vulnerability allows attackers to inject additional email headers, recipients, or malicious content that can lead to spam distribution, data exfiltration, or unauthorized communications.

In DynamoDB applications, email injection often appears in these specific scenarios:

• Profile Update Functions: Users can modify their email addresses in DynamoDB tables, potentially injecting newline characters to add CC, BCC, or Reply-To headers
• Notification Systems: Services that store email templates or recipient lists in DynamoDB attributes may be vulnerable to header injection
• Import/Export Features: CSV or bulk import functionality that processes email data before storing in DynamoDB
• Audit Trail Logging: Applications logging email transactions in DynamoDB may inadvertently store injected content

The DynamoDB-specific nature of this vulnerability stems from how applications typically structure email-related data in NoSQL schemas. Unlike relational databases with strict schemas, DynamoDB's flexible attribute model can inadvertently store malformed email data if not properly validated.

Consider this vulnerable pattern in Node.js with the AWS SDK:

async function updateUserProfile(userId, emailData) {
  const params = {
    TableName: 'Users',
    Key: { id: userId },
    UpdateExpression: 'set email = :email',
    ExpressionAttributeValues: {
      ':email': emailData.email // No validation!
    }
  };
  
  await dynamodb.update(params).promise();
  return true;
}

An attacker could supply an email like:

victim@example.com%0ACc: spammer1@example.com%0ABcc: spammer2@example.com%0AContent-Type: text/html%0A%0A<script>maliciousCode()</script>

When this data is later retrieved and used in email functions, it could send emails to unintended recipients or execute malicious content.

Detecting email injection in DynamoDB requires examining both the data stored and the application logic that processes it. middleBrick's DynamoDB-specific scanning includes several targeted checks:

1. Email Pattern Analysis: Scans DynamoDB table attributes for email fields containing suspicious characters like newline sequences (%0A, %0D), carriage returns, or multiple @ symbols
2. Attribute Validation: Examines how email attributes are defined in DynamoDB table schemas and whether they enforce proper formatting
3. Code Path Analysis: Identifies DynamoDB operations where email data flows through the application without validation
4. Template Injection Detection: Searches for email templates or notification systems that store dynamic content in DynamoDB

For manual detection, you can query your DynamoDB tables for suspicious patterns:

async function scanForEmailInjection(tableName) {
  const params = {
    TableName: tableName,
    FilterExpression: 'contains(#email, :newline) OR contains(#email, :carriageReturn)',
    ExpressionAttributeNames: {
      '#email': 'email'
    },
    ExpressionAttributeValues: {
      ':newline': '\n',
      ':carriageReturn': '\r'
    }
  };
  
  const results = await dynamodb.scan(params).promise();
  return results.Items;
}

// Scan for common injection patterns
const suspiciousEmails = await scanForEmailInjection('Users');
console.log(`Found ${suspiciousEmails.length} potentially compromised email records`);

middleBrick's automated scanning goes further by testing the actual API endpoints that interact with DynamoDB. It submits payloads containing various injection patterns and monitors how the system handles them, providing a security score with specific findings about email injection vulnerabilities.

The scanner also checks for related issues like SSRF in email processing functions and improper validation of email headers when DynamoDB data is consumed by email services.

Remediating email injection in DynamoDB applications requires a defense-in-depth approach. Here are DynamoDB-specific fixes:

1. Input Validation with DynamoDB Streams

Use DynamoDB Streams to validate email data before it's stored:

const AWS = require('aws-sdk');
const dynamodb = new AWS.DynamoDB();

exports.handler = async (event) => {
  for (const record of event.Records) {
    if (record.eventName === 'INSERT' || record.eventName === 'MODIFY') {
      const email = record.dynamodb.NewImage.email.S;
      
      // Validate email format and check for injection
      if (!isValidEmail(email) || containsInjection(email)) {
        console.log(`Invalid email detected: ${email}`);
        throw new Error('Invalid email format');
      }
    }
  }
};

function isValidEmail(email) {
  const emailRegex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
  return emailRegex.test(email);
}

function containsInjection(email) {
  const injectionPatterns = [/%0A/i, /%0D/i, /\r/i, /\n/i];
  return injectionPatterns.some(pattern => pattern.test(email));
}

2. Attribute Validation with DynamoDB's Built-in Features

Although DynamoDB doesn't have native email validation, you can use custom validation in your application layer:

class ValidatedDynamoDB {
  constructor(docClient) {
    this.docClient = docClient;
  }
  
  async putValidated(table, item) {
    if (item.email && !this.isValidEmail(item.email)) {
      throw new Error('Invalid email format');
    }
    
    const params = {
      TableName: table,
      Item: item
    };
    
    return await this.docClient.put(params).promise();
  }
  
  isValidEmail(email) {
    // Enhanced validation including injection detection
    const emailRegex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
    if (!emailRegex.test(email)) return false;
    
    // Check for newline characters
    if (email.includes('\n') || email.includes('\r')) return false;
    
    return true;
  }
}

// Usage
const validatedDB = new ValidatedDynamoDB(new AWS.DynamoDB.DocumentClient());
await validatedDB.putValidated('Users', {
  id: 'user123',
  email: 'valid@example.com',
  name: 'John Doe'
});

3. Sanitization Before Storage

Sanitize email data before storing in DynamoDB:

function sanitizeEmail(email) {
  // Remove any newline characters
  const sanitized = email.replace(/\r/g, '').replace(/\n/g, '');
  
  // Trim whitespace
  return sanitized.trim();
}

// In your update function
async function updateEmail(userId, email) {
  const sanitizedEmail = sanitizeEmail(email);
  
  if (!isValidEmail(sanitizedEmail)) {
    throw new Error('Invalid email format');
  }
  
  const params = {
    TableName: 'Users',
    Key: { id: userId },
    UpdateExpression: 'set email = :email',
    ExpressionAttributeValues: {
      ':email': sanitizedEmail
    }
  };
  
  await dynamodb.update(params).promise();
  return true;
}

4. Using middleBrick for Continuous Monitoring

Integrate middleBrick into your development workflow to catch email injection issues early:

# .github/workflows/security.yml
name: Security Scan
on: [push, pull_request]

jobs:
  security:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Run middleBrick Scan
        run: |
          npm install -g middlebrick
          middlebrick scan https://api.yourdomain.com/user-profile --fail-below B
        continue-on-error: true

This setup ensures that any email injection vulnerabilities in your DynamoDB-backed APIs are caught before deployment, with the CI/CD pipeline failing if the security score drops below your threshold.