NVD in the AI Era: The Case for Multi-Source Vulnerability Intelligence

The National Institute of Standards and Technology (NIST) has transitioned from a universal vulnerability enrichment model to a risk-based triage system due to the unsustainable increase in CVE submissions, with a significant increase from 18,000 in 2020 to over 48,000 in 2025. This shift, driven by AI advancements and the decentralization of the CVE system, emphasizes a need for more multi-source vulnerability intelligence and context, as NIST will prioritize enrichment for the most critical vulnerabilities, such as those in CISA's Known Exploited Vulnerabilities catalog, impacting legacy scanners reliant on NVD data. Snyk, an independent entity, supports this transformation through an approach that integrates multiple vulnerability sources, AI-assisted workflows, and human validation to provide actionable intelligence, emphasizing the need for context and prioritization over mere data volume. This change reflects a broader industry trend towards enhancing vulnerability intelligence to ensure security teams can make informed, prioritized decisions in an increasingly complex software landscape.

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