Network Security Monitoring: How Graph Databases See Threats That SIEM Misses

SIEM systems remain important for centralized log collection, known-signature detection, compliance reporting, and alert prioritization, but their event-centric design can miss slow, relationship-driven attacks in which no individual action exceeds an alert threshold. The discussed approach argues that graph-native network security monitoring complements SIEM by modeling connections among users, devices, accounts, IPs, domains, services, and sensitive assets, enabling analysts to trace attack paths, establish normal relationship baselines, map threat infrastructure, detect lateral movement, and enrich alerts with broader context. This relationship-focused analysis is presented as particularly useful against lateral movement, insider threats, supply-chain compromises, and living-off-the-land techniques, which often appear legitimate when viewed as isolated events. TigerGraph is positioned as a platform for real-time graph-based threat detection and AI-assisted security operations, with MCP Server and GraphRAG capabilities intended to let SOC tools and agents investigate connected data, provide traceable reasoning, and reduce manual alert-triage work.

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