L1shed/Turbo

AI Summary: Implement an AI/ML model for real-time detection of abnormal network traffic (intrusion, DDoS, etc.) in a distributed residential proxy network. The model should use anonymous connection data (packet sizes, intervals, durations) and be trained on a dataset of normal traffic. Consider using unsupervised learning methods like Isolation Forest or KitNET, and explore data-driven development with Kafka.

AI Summary: Implement client-side metrics collection for the Turbo project, sending anonymized data (timestamp, OS, country code, ping) to the server via a web request on launch and optionally through the QUIC connection. The server will then log this data via a Discord webhook, marking new clients.