Lightning Talk: Revolutionize Security GRC: Leverage AI and LLM for Continuous Control...
summary
Claims a pipeline that converts PDFs to YAML (example: NSA Kubernetes hardening) and builds a Neo4j graph that links a GRC schema to a system schema, correlating evidence from scanners like Trivy/Snyk and inventory tools to surface focused risks rather than noise. Uses LLMs to turn natural queries into GraphQL, deploys Google Forms for continuous evidence collection, applies CEL for dynamic scoring (example outputs: cluster 50% NSA, 60% MITRE) and reports to dashboards and chatops for operational governance.
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chapters (7)
- 0:00Introduction
- 1:03GRC team challenges
- 3:58AI and LLM for GRC
- 6:03Graph models for GRC
- 7:28Benefits of graph and LLM
- 8:56Summary
- 11:03Q&A on LLM hallucinations
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