Protects hosted web applications from attacks that target known and unknown exploits
Correlated threat detection with AI-based behavioral scanning
Up to 20 Gbps protected WAF throughput
Enhanced protection with Fortinet Security Fabric integration
Visual analytics tools for advanced threat insights
Third-party integration and virtual patching
Web Application Firewall with Dual AI-based Machine Learning Engines
FortiWeb is a web application firewall (WAF) that protects hosted web applications from attacks that target known and unknown exploits. Using AI-enhanced multi-layer and correlated detection methods, FortiWeb defends applications from known vulnerabilities and from zero-day threats.
Acceleration and Performance
Multi-core processor technology combined with hardware-based SSL tools deliver blazing fast protected WAF throughput.
Protection from the OWASP Top Ten application attacks including Cross Site Scripting and SQL Injection.
AI-based Machine Learning Threat Detection
Dual-layer machine learning engines are employed to detect application request anomalies and determine if they are threats.
Comprehensive Web Application Security with FortiWeb
Using an advanced multi-layered and correlated approach, FortiWeb provides complete security for your external and internal web-based applications from the OWASP Top 10 and many other threats. At the heart of FortiWeb is AI-based detection engine that uses machine learning to identify requests that stray from normal patterns and takes action to protect applications from known and unknown zero-day threats.
Dual-Layer Machine Learning Powered by FortiGuard Labs
Although Web Application Firewalls are the best defense against attacks that target web-based applications, WAFs can be tedious and time-consuming to fine tune to prevent unwanted false positive detections. FortiWeb solves this challenge using an AI-based machine learning approach that employs two separate detection engines.
The first automatically and dynamically monitors all application elements for activity that strays from predicted entries. If this first engine flags what it determines is an anomaly, it is then sent to the second machine learning layer to assess if it is a threat or simply a benign variance such as a typo or new character that hasn t been seen previously. If it is an attack, then FortiWeb can take actions such as logging, alerting and/or blocking the request. The second machine learning layer uses threat models that are included as part of the FortiWeb solution and are updated with the FortiGuard WAF Security Service to provide protection from new threats that require model retraining and testing.
Deep Integration into the Fortinet Security Fabric and Third-Party Scanners
As the threat landscape evolves, many new threats require a multi-pronged approach for protecting web-based applications. Advanced Persistent Threats that target users can take many different forms than traditional single-vector attack types and can evade protections offered only by a single device. FortiWeb s integration with FortiGate and FortiSandbox extend basic WAF protections through synchronization and sharing of threat information to both deeply scan suspicious files and share infected internal sources.
FortiWeb also provides integration with leading third-party vulnerability scanners including Acunetix, HP WebInspect, IBM AppScan, Qualys, IBM QRadar, and WhiteHat to provide dynamic virtual patches to security issues in application environments. Vulnerabilities found by the scanner are quickly and automatically turned into security rules by FortiWeb to protect the application until developers can address them in the application code.
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