Netskope’s Threat Detection architecture comprises multiple scanning engines to handle different stages of content analysis. The “Fast Scan” component is specifically associated with Machine Learning-based detection, which allows the platform to rapidly classify files and content based on learned behavioral patterns without requiring the overhead of signature lookups or full dynamic analysis. Machine Learning enables high-throughput detection suitable for real-time inline inspection of traffic at scale. Heuristic Analysis is a separate component used for deeper behavioral evaluation, while Dynamic Analysis (sandboxing) is reserved for unknown or suspicious files requiring execution in an isolated environment. Static Analysis involves examining file structure without execution and represents a different scanning mode from the Fast Scan component.