Endpoint detection and response made one thing easy: collecting data. EDR agents capture a torrent of telemetry from every endpoint — process activity, file operations, network connections, system events. But collection was never the hard part. The hard part is what comes after: turning that mountain of data into a verdict, finding the small number of genuinely threatening events among the overwhelming mass of benign ones. The data is the raw material; analysis is where it becomes security.
The grant US12231443B2, "Analysis of endpoint detect and response data" (issued February 18, 2025, assigned to Musaruba US LLC), is squarely about that second problem. Its CPC classifications are concise and pointed — the intrusion-detection classes H04L 63/1416 and H04L 63/1425, plus the machine-learning class G06N 20/00 — describing analysis applied to EDR telemetry.
The mechanism worth understanding is the application of machine learning and correlation to make sense of the volume. Manual analysis of EDR data at scale is hopeless; there's simply too much of it. Learned models and correlation logic do the work of surfacing the patterns that indicate a threat — connecting related events across the telemetry, distinguishing the benign-but-unusual from the genuinely malicious, and presenting analysts with a manageable set of leads rather than an undifferentiated flood.
For defenders, the practical takeaway is that the value of EDR lives in the analytics, not the agent. Two organizations can run the same EDR agent and get wildly different security outcomes depending on how well the collected data is analyzed. The agent is necessary but commoditized; the analysis is where threats are actually caught or missed.
The recurring challenge — true across this whole generation of detection technology — is doing the analysis well enough to be both accurate and operationally usable, surfacing real threats without burying analysts in false positives. The patent reflects the field's center of gravity having shifted decisively from collecting endpoint data to making sense of it, which is where the difficulty, and the defensive value, now lies.