WAF is a network security solution that monitors and filters web traffic between the Internet and applications at the OSI model’s application layer (L7). It blocks malicious requests using predefined security rules designed to protect against known vulnerabilities and attack patterns.
WAF helps defend against various attack types that other technologies might not handle effectively. WAF enables fast and effective mitigation of sophisticated attacks
Attacker injects malicious SQL code into a query to gain access to databases
Attacker exploits HTTP protocol vulnerabilities to manipulate a user’s browser into performing actions on their behalf
Attacker injects malicious scripts into a web page, which execute when a user visits the compromised page
All protection components are hosted within Kaspersky DDoS Protection’s cloud infrastructure, eliminating the need for time-consuming installation and maintenance of security elements. The system is managed entirely through a web interface.
Machine learning-based model automatically monitors and analyzes all inbound requests to the protected resource, collecting detailed statistical data
Based on collected data, the system creates behavioral templates of legitimate users and generates filtration rules to detect and protect against even the most sophisticated attacks
WAF blocks DDoS attacks, bots, and hackers while allowing only legitimate users to access the protected resource
Implementing WAF significantly reduces risks of data breaches or web service downtime. Therefore, WAF is essential for protecting mission-critical web applications with complex architectures:
Our cloud-based solution that doesn’t restrict user application access while providing full functionality of a traditional WAF
Access our round-the-clock web portal to easily manage client accounts, adjust security settings, and monitor threats in real-time
Protection against all types of L7 attacks through customizable rules tailored for each protected resource
All security components are cloud-hosted, eliminating installation and maintenance costs
Machine learning model establishes legitimate user behavior patterns, which are essential for detecting sophisticated attacks and enhancing system effectiveness
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