VeilGuard: A Multi-Modal AI Framework for Detecting Hidden Communications, Covert Payloads, and Emerging Cyber Threats

VeilGuard presents a multimodal artificial intelligence framework for identifying hidden communications, covert payloads, and emerging cyber threats across heterogeneous digital content. The proposed architecture combines AI-driven content analysis, anomaly detection, contextual reasoning, and explainable threat assessment to identify patterns that may evade conventional security controls. The framework is designed to support cybersecurity analysts and organizations in detecting increasingly sophisticated forms of concealed or obfuscated communication while maintaining human oversight and interpretable decision support. This paper presents the conceptual architecture, analytical workflow, security applications, and future research direction for VeilGuard as an AI-assisted cybersecurity framework.