AWS WAF architecture protecting fintech applications with CloudFront and ECS Fargate
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AWS WAF Best Practices for Fintech Applications

Production-tested AWS WAF best practices for securing fintech applications, including recommended architecture, managed rule groups, CloudFormation configuration, monitoring, and common pitfalls to avoid.

SP
Saurabh Parmar
Author
3 min read

AWS WAF Best Practices for Fintech Applications

Securing fintech applications requires defense-in-depth strategies. After implementing AWS WAF for multiple financial services clients, here's what actually works in production.

Why Fintech Needs WAF

Fintech applications handle sensitive financial data and are prime targets for attacks. A single breach can mean regulatory penalties, lost customer trust, and significant financial damage. AWS WAF provides a critical security layer between your application and the internet.

Key threats WAF protects against:

  • SQL injection attacks targeting transaction databases
  • Cross-site scripting (XSS) attempts to steal session tokens
  • Credential stuffing against login endpoints
  • API abuse from automated bots

The most effective pattern attaches AWS WAF to a CloudFront distribution in front of your Application Load Balancer and ECS Fargate services.

Traffic flow: Internet → CloudFront → WAF WebACL → ALB → ECS Fargate

Why WAF on CloudFront instead of ALB:

  • Global edge protection - malicious traffic blocked at edge locations before reaching your region
  • Better DDoS resilience - leverages CloudFront's built-in protections
  • Performance benefits - caching and edge termination reduce latency

Essential Managed Rule Groups

A focused set of managed rule groups provides strong coverage with minimal false positives:

  1. AWSManagedRulesCommonRuleSet - OWASP Top 10 and common vulnerabilities
  2. AWSManagedRulesSQLiRuleSet - SQL injection protection
  3. AWSManagedRulesKnownBadInputsRuleSet - Known malicious patterns
  4. AWSManagedRulesLinuxRuleSet - Linux-specific exploits

Avoid enabling every available rule group. Each extra rule adds latency and increases the chance of false positives.

Monitoring and Alerting

Effective WAF deployment requires proper observability. Key CloudWatch metrics to monitor:

  • BlockedRequests - tracks attack attempts; alert when exceeding 3x baseline
  • AllowedRequests - sudden drops may indicate legitimate traffic being blocked
  • CountedRequests - use during rule testing before switching to Block mode

Integrate WAF logs with your SIEM for correlation with other security events.

Common Pitfalls to Avoid

  1. Starting in Block mode immediately - Always deploy new rules in Count mode first for 1-2 weeks
  2. Forgetting health check exclusions - Add rules to allow ALB health checks
  3. Not handling JSON API false positives - Tune rules for your specific API patterns
  4. Missing rate-based rules - Add rate limiting (2000 req/5min per IP) for brute force protection
  5. Ignoring geographic patterns - Consider geo-blocking countries you don't serve

Production Results

After implementing this architecture for a fintech payment processing client:

  • 50,000+ malicious requests blocked in the first month
  • Zero false positives after proper tuning
  • 99.97% uptime maintained during targeted attacks
  • PCI DSS compliance requirements satisfied

Key Takeaways

AWS WAF is not a set-and-forget solution. Regular review and tuning based on your application's traffic patterns will maximize protection while minimizing false positives. Start with the recommended managed rule stack, deploy in Count mode first, and iterate based on observed patterns.