Weak on residential proxy attribution & AI-driven bot detection. Traffic can easily look like a “real user” from a residential IP. Rules are either too permissive or risk blocking legitimate users.

Evaluates the individual session and detailed IP attributes, enabling you to intelligently increase user friction or deny risky sessions for smarter edge enforcement.

Lack of session-level anonymization detection and attribution. May harm conversion or interfere with desirable agentic automation.

Most granular detail into specific residential/ malware proxy networks links tradecraft across campaigns and allows for targeted user friction or alerts.

High rates of false positives for VPN and residential proxy detection. Less accurate for security and fraud use-cases. Privacy concerns and considerations.

Highest-level accuracy in session-level VPN and residential proxy detection vs. traditional browser and device attribute tracking with security features tacked on.

Providers often rely on incorrect or self-reported data. VPNs and proxies are used to hide the end-user location creating a mismatch between stated and actual location.

Accurate geolocation with geo-mismatch detection beats self-reported data with no VPN/proxy context.

Focused on inside-out connections; not outside-in. Misses the “clean” last-mile IPs used for inbound attacks.

Accurate identification of VPN/proxy service that an IP/session is using, plus tunnel entry/exit context, device/ connection type, usage concentrations, and client behaviors.