Graph Algorithms for Cybersecurity: FalkorDB Webinar Insights

Software architects and senior developers who work on generative AI systems and related technologies can benefit from the FalkorDB webinar, "Advanced Graph Algorithms in FalkorDB: Cybersecurity Focus," which illustrates the use of graph databases in threat modeling, dependency analysis, and data-leakage estimation. The webinar features three demonstrations: the first simulates the propagation of WannaCry v2 using a Monte-Carlo approach to assess infection probabilities, aiding in adaptive threat modeling; the second employs a Maven dependency graph to identify indirect paths to vulnerabilities like Log4j, automating the detection of transitive vulnerabilities; and the third uses max-flow modeling to compute data exfiltration rates on a network, providing insights for risk-based access control. These demonstrations showcase reusable graph-algorithm patterns that can be integrated into AI-driven security frameworks, leveraging graph primitives and user-defined functions to create transparent and measurable defenses in systems such as LLMs and GraphRAG pipelines.