ARCHIVES

Academic institutions increasingly hold data and infrastructure worth targeting, yet most lack a dedicated Security Operations Center capable of turning raw threat intelligence into advisories that are actually distributed to and acted on by their community. Existing Security Information and Event Management stacks handle log aggregation, and threat-intelligence platforms handle indicator storage, but neither produces institution-tailored, human-readable bulletins or delivers them across the channels an institutional audience actually uses. This paper presents the design and implementation of LAADS (LLM-Augmented Advisory Authoring and Dissemination System), a sector-aware security advisory platform built for this gap: a five-layer web system that authors advisories through three entry paths (manual authoring, AI-assisted extraction from a submitted article, and escalation of an external feed item), enforces sector-scoped multi-tenancy across five operational sectors at four independent layers, correlates advisories against an institutional asset inventory through a three-tier matching engine, and disseminates published advisories over six channels spanning real-time push, e-mail, chat webhooks, PDF export and share links. We describe the architecture, data model and enforcement mechanisms in detail and report functional verification of each subsystem. Quantitative evaluation of enrichment performance under production load is left as future work.