URL Filtering inline ML enables the firewall
dataplane to apply machine learning on webpages to prevent malicious
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
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.