As with signature analysis, it is required that the WAF be tied to a threat intelligence and response service that ensures that blacklists are updated frequently. More sophisticated WAFs can identify and blacklist the sources of malicious packets detected by the signature engine.
When multiple web applications interact with each other using different communication protocols, vulnerabilities arise. An attack can bypass the protection of one application by imitating the protocol of another. To prevent such exploits, a WAF must check the protocol of any HTTP code that the protected application attempts to execute.
Integration. A WAF must integrate all of the security features it implements, primarily through data correlation: application-level signature data, data on malicious bots, suspicious IP addresses, and new viruses must be compared so that threat information becomes available to all components of the information security system.
Security data sharing. Many cyberattacks are multi-vector and use kenya whatsapp data malware simultaneously. Combating them requires sharing data from all network components in real time. For example, an attack might target vulnerabilities in endpoints, email, and cloud services, and use machine learning to fine-tune exploits based on the information it receives in the process. A WAF must be able to use real-time threat information from each security component protecting the attacked nodes and services and block such sophisticated attacks.
Throughput. Few customers can afford to slow down network traffic when a WAF operates with blacklists, whitelists, and behavioral profiles. WAF selectors should consider not only the average throughput of the solution when performing these operations, but also network characteristics and corporate information security system architecture that can reduce WAF throughput in a specific IT environment.