URL Filtering Inline ML

URL Filtering inline ML enables the firewall dataplane to apply machine learning on webpages to prevent malicious variants of JavaScript exploits and phishing from entering your network. Inline ML dynamically analyzes and detects malicious contents by evaluating various web page details using a series of ML models. Each inline ML model detects malicious content by evaluating file details, including decoder fields and patterns, to formulate a high probability classification and verdict, which is then used as part of your larger web security policy. URLs classified as malicious by inline ML are forwarded to PAN-DB for additional analysis and validation. To keep up with the latest changes in the threat landscape, inline ML models are updated regularly and are added via content releases. The URL Filtering inline ML models are configured through your URL filtering profile and requires a PAN-DB URL filtering license. Additionally, you can also specify URL exceptions to exclude any false-positives that might be encountered. This allows you to create more granular rules for your profiles to support your specific security needs.
Inline ML-based protection can also be enabled to detect malicious PE files and PowerShell scripts in real-time as part of your Antivirus profile configuration. For more information, refer to: WildFire Inline ML
URL Filtering inline ML is not supported on the VM-50 or VM50L virtual appliance.

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