Brute Force Attack on Aws

Brute force attacks in Aws applications typically exploit authentication endpoints and API access controls. In a typical Aws-based application, attackers target login routes, API keys, or token endpoints to gain unauthorized access through repeated guessing attempts. The nature of serverless architectures and microservices can actually amplify this risk—each function invocation might represent a separate authentication attempt that bypasses traditional rate limiting mechanisms.

Common manifestations include credential stuffing attacks against Cognito user pools, where attackers use breached username/password combinations to test against your authentication endpoints. Another pattern involves API Gateway endpoints without proper throttling, allowing attackers to hammer authentication endpoints at scale. Lambda functions triggered by API Gateway may also be vulnerable if they lack internal rate limiting, as each invocation consumes resources and could potentially reveal information through timing attacks or error messages.

Real-world examples show attackers targeting specific Aws services: DynamoDB tables exposed without proper IAM controls, S3 buckets with weak or default credentials, and Lambda functions with overly permissive execution roles. The distributed nature of Aws means attackers can distribute their attempts across multiple availability zones or regions, making detection more challenging without proper monitoring.

Detecting brute force attacks in Aws environments requires monitoring across multiple services and understanding Aws-specific attack patterns. CloudWatch Logs and CloudTrail provide the foundational data for identifying suspicious authentication patterns. Look for multiple failed authentication attempts from the same IP address, unusual geographic access patterns, or credential usage at abnormal times.

CloudWatch Insights queries can help identify brute force patterns. For example, this query detects excessive failed logins to a Cognito user pool:

fields @timestamp, eventSource, eventName, errorCode, sourceIPAddress
| filter eventSource = "cognito-idp.amazonaws.com" and eventName = "InitiateAuth" and errorCode = "NotAuthorizedException"
| stats count(*) as failedAttempts by sourceIPAddress, bin(5m)
| filter failedAttempts > 10
| sort @timestamp desc

API Gateway provides built-in throttling that can help detect and prevent brute force attacks. Configure usage plans with rate limits and quotas. Monitor the 4XXError metrics in CloudWatch to identify excessive authentication failures. The IntegrationLatency metric can also reveal timing attacks where attackers measure response times to infer valid credentials.

For Lambda functions, enable X-Ray tracing to understand invocation patterns and identify abnormal traffic. Set up CloudWatch alarms on Throttles and Errors metrics. The middleBrick scanner specifically tests for brute force vulnerabilities by attempting multiple authentication requests and analyzing response patterns, including lockout mechanisms, rate limiting headers, and timing consistency.

Remediating brute force vulnerabilities in Aws requires a defense-in-depth approach using native Aws services. Start with Cognito user pools, which provide built-in protections. Configure PasswordPolicy with minimum length, complexity requirements, and temporary password expiration. Enable automatic account lockout after a configurable number of failed attempts:

const userPool = new cognito.CfnUserPool(this, 'UserPool', {
  policies: {
    passwordPolicy: {
      minimumLength: 12,
      requireLowercase: true,
      requireUppercase: true,
      requireNumbers: true,
      requireSymbols: true,
      temporaryPasswordValidityDays: 7
    }
  },
  accountRecoverySetting: {
    recoveryMechanisms: [{
      name: 'verified_email',
      priority: 1
    }]
  },
  autoVerify: {
    email: true
  },
  mfaConfiguration: 'OPTIONAL',
  adminCreateUserConfig: {
    allowAdminCreateUserOnly: false
  }
});

Implement API Gateway throttling at the resource level. Configure usage plans with rate limits and quotas specific to authentication endpoints:

const authUsagePlan = new apigateway.UsagePlan(this, 'AuthUsagePlan', {
  name: 'AuthRateLimiting',
  description: 'Limits authentication attempts',
  throttle: {
    burstLimit: 5,
    rateLimit: 1
  },
  quota: {
    limit: 100,
    period: apigateway.Period.DAY
  }
});

For Lambda functions, implement distributed rate limiting using DynamoDB with conditional writes. This pattern prevents multiple functions from processing the same request simultaneously:

const ddb = new AWS.DynamoDB.DocumentClient();
const checkRateLimit = async (ipAddress) => {
  const params = {
    TableName: 'RateLimitTable',
    Item: {
      ipAddress: ipAddress,
      ttl: Math.floor(Date.now() / 1000) + 60 // 1 minute window
    },
    ConditionExpression: 'attribute_not_exists(ipAddress)'
  };
  
  try {
    await ddb.put(params).promise();
    return true; // Allowed
  } catch (err) {
    if (err.code === 'ConditionalCheckFailedException') {
      return false; // Rate limited
    }
    throw err;
  }
};

Enable WAF (Web Application Firewall) with rate-based rules to protect against distributed brute force attacks. Configure rules to trigger based on request rates from specific IP addresses or geographic regions. Combine this with CloudFront for edge-based protection before requests reach your API Gateway endpoints.