AI Detection
Detection that does not depend on the provider.
Patronus recognizes AI traffic by how a connection behaves, not by the provider's name. New tools, internal models and unknown services show up the moment they are used.
Go to Desktop AppLive classification
Real time01
Verified Performance
Detection that stays fast when the traffic gets unfamiliar.
<10 ms
per AI detection
Obfuscated
AI transports detected
<100 MB
peak RAM
100+
AI connections tested
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Pre-TLS to Tool-Call Signals
See AI traffic before it blends into normal network traffic.
Patronus starts before TLS, then correlates endpoint, protocol, header, payload, process-origin and cadence signals into one provider-agnostic classification layer. Correlated AI fingerprints help identify known, unknown and obfuscated transports in the same pass.
One Detection Layer
A shared language for signals that used to live in separate silos.
The engine is designed to remain stable as providers, models, apps and agent frameworks change.
Signals in the correlation pass
Destination / SNI / Port / Protocol / Headers / Payload / Tool calls
Before TLS
Start with metadata that survives encryption: destination, SNI, port, process-origin and cadence.
Across protocols
Layer endpoint, header, payload and tool-call evidence to separate behavior from signatures.
Correlated AI fingerprints
Behavioral fingerprints across payloads and transport patterns help identify AI traffic even when providers or APIs change.
Provider-agnostic
One detection engine for every AI provider.
Classification works on traffic behavior, not on a signature. When a provider changes its API or a new tool appears, detection stays stable.
Try Patronus on your own computer.
Detect known, unknown and obfuscated AI communication in real time.
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AI Detection FAQ
Clear answers about pre-TLS detection, on-device classification and signal coverage.