Hillstone W-Series Web Application Firewall

Additional Info

CompanyHillstone Networks
Websitehttp://www.hillstonenet.com
Company size (employees)1,000 to 4,999

Overview

Hillstone W-Series Web Application Firewall (WAF) provides enterprise-class, comprehensive security for web servers, applications and APIs. It defends against attacks at both the network and application layers, providing protections against DDoS, the OWASP Top 10 threats, and bot attacks, for example. In addition, the WAF validates APIs against the schema defined in OpenAPI, and automatically generates positive security model policies to detect and defend against attacks and misuse.

Hillstone WAF combines traditional rules-based detection with innovative semantics analysis. This dual-engine approach significantly increases accuracy while minimizing false positives. Hillstone WAF also leverages machine learning technology to fine tune security policies and block unknown threats and attacks. Further, logs can be automatically aggregated across multiple dimensions to allow admins to easily identify suspicious anomalies or locate false positives, and then further refine policies as needed.

How we are different

Comprehensive Web Application Security
Hillstone Web Application Firewall (WAF) provides complete security of web-based applications and APIs for enterprises and other organizations. It detects and defends against attacks at both the network layer (such as DDoS attacks, flood attacks, scan and spoof, etc.), and at the application layer (such as the OWASP Top 10 risks including injection attacks, cross site scripting (XSS) attacks, injection, etc). Hillstone WAF automatically discovers web servers and related assets and puts them under protection. With this capability, Hillstone WAF covers the entire web estate even when it scales, which helps improve operational efficiencies and deliver faster time-to-value.


Improved Detection Accuracy and Efficiency with Dual Engines
Hillstone WAF integrates the industry’s most innovative semantics analysis with traditional WAF detection engines. Combined with traditional rules-based detection, the semantics analysis engine helps further detect threats like SQL injection and cross site scripting, and minimizes false positives. Hillstone WAF’s recursive decoding capability also detects attacks that are obscured by multiple encoding. This dual-engine approach significantly improves the accuracy of detection and efficiency in operation.


Machine-Learning-Driven Security Rule Optimization and Unknown Attack Defense
In addition to general protection based on rules and scripts for known attacks, Hillstone WAF’s auto-learning capability helps mitigate never-before-seen exploits to protect specific applications from zero-day attacks. Its ML-based model learns from the data of normal traffic such as parameter length, cookie, HTTP methods, etc., tunes itself based on the test results as well as input from administrators, and continues updating the learning models and optimizing WAF rules as applications evolve. It significantly reduces operational overhead by eliminating the troubleshooting of false positives and manual policy tuning.