SocialCipher: A Multimodal Framework for Proactive Threat Detection with Sentintel

The widespread use of social media platforms presents significant challenges for threat detection, as malicious actors exploit multimodal communication-text, emojis, memes, and idiomatic expressions-to conceal harmful intent. We present SocialCipher, an AI-driven architecture for preemptive threat detection that integrates a custom threat framework, robust filtering mechanisms, and SentIntel GPT (4.0), a transformer model optimized for multimodal analysis. SocialCipher categorizes threats across six dimensions-cyber, physical, reputational, operational, regulatory, and psychological/emotional-enabling risk scoring aligned with government classification levels. Empirical evaluations of SentIntel GPT against ten contemporary AI models (including GPT 3.5, GPT 4.0, Claude, and Mistral variants) show it achieves 96 % accuracy, confirming its ability to interpret complex inputs. These findings highlight SocialCipher's potential to improve real-time threat detection and support proactive interventions in dynamic digital ecosystems.