Cienaga Systems' Genetically Engineered Cyber Security (GECS) is a network anomaly detection technology that uses an evolutionary, genetics-inspired approach to maintain detector effectiveness over time against increasingly sophisticated attackers. Unlike traditional anomaly detectors — which suffer from rapid obsolescence similar to signature-based and heuristics-based systems — GECS continuously tests mutated attack scenarios against a hypothetical attack surface. When new successful attacks are discovered through this process, new detectors are evolved in response, keeping detection capabilities current without manual updates. The technology draws on techniques from game theory, machine learning, statistics, and data visualization. It models adversarial versus collaborative network interactions, establishes peer group reputation scoring, and assesses the risk posture of individual hosts within a network. These capabilities are designed to augment the analytical process used by human security analysts when reviewing network activity. Comparative performance data presented by Cienaga demonstrates that, over time, an evolving attacker's success rate remains suppressed against a GECS detector, whereas a standard anomaly detector degrades in effectiveness as the attacker adapts.