Layer 2 Detection takes forensic analysis to the next level, going beyond initial red flag identification to perform advanced correlation, threat attribution, and behavioral analysis. It leverages the foundational data from Layer 1—already aggregated and cleaned—and dives deeper into multi-event relationships, uncovering complex attack chains, lateral movement patterns, and coordinated multi-vector attacks. Layer 2 intelligently correlates user activities, device interactions, and network traffic across extended timelines, identifying hidden threats that evade traditional detection methods. By incorporating enriched threat intelligence, Layer 2 Detection can attribute attacks to known hacking groups, state-sponsored actors, or insider threats. The result is a comprehensive, high-fidelity threat narrative that allows forensic service providers and law enforcement to connect devices, users, and incidents with unprecedented accuracy—helping investigators not just detect, but fully understand how, when, and why an attack occurred while providing the evidentiary backbone for legal proceedings and organizational response.

Layer 2 Detection correlated over 50 events across endpoints, cloud environments, and network infrastructure in minutes, revealing hidden lateral movements, unauthorized data transfers, and insider threats that traditional systems often miss. The platform linked patient zero, attack vectors, and threat actors with ease, offering forensic examiners and law enforcement a clear and actionable threat narrative without spending hours sifting through millions of logs.