Encrypted Command and Control: Can You Really Cover Your Tracks? by Luke Richards

This Vectra AI blog post outlines the challenge of detecting encrypted command-and-control (C2) channels in a TLS-dominant internet and summarizes how granular time-series flow metadata combined with supervised machine learning (Random Forests, RNNs, and LSTMs) can be used to identify C2 behaviors, emphasizing model development, data quality, and analyst workflows rather than reporting a specific security incident.