The Core Challenge
Signature-based security is always playing catch-up. A zero-day exploit, by definition, has no known signature. We needed a fundamentally different approach for SecureWeb.ai.
Behavioral Baselines
Our ML pipeline establishes a behavioral baseline for every protected application by analyzing traffic patterns over a 14-day window. It learns: what endpoints are called, at what frequency, from what geolocations, with what payload shapes.
Anomaly Scoring
Once a baseline is established, every incoming request is scored against it in real-time. A score above the threshold triggers an alert. Above a higher threshold, the request is automatically blocked.
The Results
In our first six months of production, SecureWeb.ai detected 847 genuine threats that signature-based tools missed entirely — including two coordinated attack campaigns that targeted multiple customers simultaneously.