ML-powered WAF that learns from attacks. Protect your web applications from OWASP Top 10 threats with intelligent, adaptive security that gets smarter over time.
Our WAF uses machine learning to detect and block threats in real-time, protecting against both known vulnerabilities and zero-day exploits.
Detects and blocks malicious SQL queries attempting to manipulate your database. Uses pattern matching and semantic analysis to identify injection attempts.
Prevents injection of malicious scripts into web pages. Sanitizes user input and blocks reflected, stored, and DOM-based XSS attacks.
Validates request origins and tokens to prevent Cross-Site Request Forgery. Ensures only legitimate requests are processed.
Blocks attempts to execute arbitrary code on your servers. Detects command injection, file inclusion, and deserialization attacks.
Protects authentication mechanisms from credential stuffing, brute force, and session hijacking attacks.
Plus protection from XXE, insecure deserialization, security misconfiguration, sensitive data exposure, and insufficient logging.
Traditional WAFs rely on static rules that attackers can bypass. Our ML-powered WAF analyzes traffic patterns, learns normal behavior, and automatically detects anomalies—even zero-day exploits.
Creates baseline of normal traffic patterns and flags deviations that indicate attacks.
Model improves over time by learning from new attack patterns across our global network.
Automatically adjusts protection as new threats emerge, without manual rule updates.
Native integration with ALB, CloudFront, and API Gateway
Works with GCP Load Balancer and Cloud Armor
Ingress controller with automated certificate management
Export logs to Splunk, ELK, Datadog, and more