Understanding WAF Technology and Architecture

Web Application Firewalls differ fundamentally from traditional firewalls in their approach to security. While network firewalls focus on ports, protocols, and IP addresses, WAFs analyze the actual content of HTTP requests and responses. This deep inspection capability allows WAFs to understand application logic, detect malicious payloads hidden in seemingly legitimate traffic, and protect against attacks that exploit application vulnerabilities rather than network weaknesses.

The architecture of a WAF typically includes several key components working together. The parsing engine deconstructs HTTP traffic into its constituent parts - headers, parameters, cookies, and body content. The detection engine applies various techniques including signature matching, behavioral analysis, and anomaly detection to identify threats. The decision engine determines what action to take based on detected threats and configured policies. Finally, the response engine either blocks malicious requests, sanitizes them, or allows them through while logging for analysis.

Modern WAFs employ multiple detection methodologies simultaneously. Signature-based detection identifies known attack patterns, similar to antivirus software. This approach effectively blocks well-documented attacks but struggles with zero-day exploits or obfuscated payloads. Behavioral analysis establishes baselines of normal application behavior and flags deviations that might indicate attacks. Machine learning algorithms increasingly enhance WAF capabilities, learning from traffic patterns to improve detection accuracy and reduce false positives over time.