AI Security
Enterprise AI Security
Machine learning models trained to detect zero-day threats instantly.
The Challenge
Signature-based firewalls cannot detect novel attacks or subtle logic abuse. Attackers mutate payloads to evade static rules.
The ZTLayer Solution
We leverage behavioral models and neural networks trained on trillions of global requests to identify malicious intent, even if the payload has never been seen before.
Architecture
Traffic metadata is streamed asynchronously to our ML cluster. Models evaluate request patterns, user-agent anomalies, and timing attacks. Suspicious behavior dynamically adjusts the IP trust score in our edge Redis cache.
Best Practices
- Keep the AI confidence threshold at "High" for automatic blocking.
- Review anomalous traffic logs weekly.
- Train the model further by flagging false positives in the dashboard.
Enterprise Use Cases
- Protecting against novel CVEs before patches exist.
- Identifying credential stuffing campaigns.
- Stopping slow-rate distributed layer 7 attacks.
Ready to secure your infrastructure?
Deploy AI Security in less than 5 minutes using our SDKs.