Financial systems are not isolated, they synchronize with each other and are highly influenced by external domains such as social media, news cycles, and global events. These cross-domain influences can accelerate bubbles, trigger instability, and disrupt markets. We develop methods to detect such vulnerabilities early, by analyzing correlations in timing, behavior, and information flow across institutions and platforms. Using tools from network theory and machine learning, we aim to reveal hidden dependencies and anticipate emergent risks in financial systems.