AGS-INTEL: Authentic & Granular Source for Data Breach Intelligence

Abstract

As artificial intelligence reshapes the cybersecurity landscape, the demand for a trustworthy, real-time intelligence platform to track security incidents has become mission-critical. This paper proposes AGS-INTEL, an AI-driven platform designed to revolutionize data breach intelligence by providing a credible, real-time repository that consolidates, verifies, and contextualizes global security incidents. Unlike traditional databases, AGS-INTEL employs a validated scoring algorithm and enriched metadata to capture breach dimensions (legal, technical, sectoral, geopolitical), drawing from GDPR/HIPAA disclosures, threat intelligence, dark web forums, and academic reports, among other sources. Utilizing NLP and agentic AI, it extracts structured metadata from unstructured narratives while integrating ethical data scraping, regulatory compliance, and cross-jurisdictional filtering to ensure high fidelity. A visual analytics dashboard empowers stakeholders, including regulators, policymakers, cybersecurity professionals, and journalists, to analyze breach trends by industry, geography, and threat modality, enhancing transparency and risk governance. By delivering authenticated, actionable data, AGS-INTEL addresses critical gaps in existing tools, setting a new standard for ethical AI in breach intelligence and strengthening societal resilience against escalating cyber threats.