What is Runtime Threat Analytics?

Understanding Runtime Threat Analytics

Runtime Threat Analytics focuses on detecting malicious behavior by continuously monitoring application execution patterns rather than relying on pre-defined signatures or static code analysis. This approach recognizes that modern threats often exploit legitimate functionality or previously unknown vulnerabilities that traditional security tools miss. By establishing baselines of normal application behavior and identifying deviations, these systems can detect subtle indicators of compromise like unusual data access patterns, suspicious process relationships, or anomalous network connections. Advanced implementations leverage machine learning to improve detection accuracy over time, differentiating between benign anomalies and genuine threats. This capability proves particularly valuable for detecting sophisticated attacks like fileless malware, living-off-the-land techniques, or zero-day exploits that bypass traditional preventive controls. Organizations typically deploy runtime analytics as a complementary layer alongside traditional security tools, focusing particularly on protecting critical applications handling sensitive data. Effective implementation requires careful tuning to establish accurate baselines, integration with existing security monitoring for context enrichment, and response procedures for addressing detected anomalies.