Correlation engine-analyzes incoming traffic and triages it using known attack signatures, AI/ML analysis, application profiling and custom rules to determine if it should be blocked or not.This is important to allow customization of WAF behavior and avoid blocking legitimate traffic. Customization engine-the WAF allows operators to define security rules specific to the organization or web application, and instantly applies them to application traffic.This can help identify abnormal or malicious requests and block them. Application profiling-the WAF analyzes web application structure, including URLs, typical requests, allowed data types and values.This makes it possible to identify attacks even if they do not match a known malicious pattern. They identify baselines for specific types of traffic, and capture anomalies that might represent an attack. AI/ML analysis of traffic patterns-modern WAFs perform behavioral analysis of traffic using artificial intelligence algorithms.In the past, WAFs primarily relied on databases of attack patterns, but this technique is largely ineffective against new and unknown attacks. They can include known malicious IPs, types of requests, unusual server responses, and more. Attack signature database-these are patterns that can be used to identify malicious traffic.WAFs typically provide the following capabilities:

Waf network