Most approaches to cybersecurity detect threats only after they manifest in observable attacks. Our research shifts the focus to the coordination stage, where malicious actors organize activity across fragmented and encrypted environments. To detect these early signals, we combine deep learning, network theory, and temporal modeling to identify subtle patterns of synchronized activity that would otherwise remain invisible. This proactive perspective opens new possibilities for safeguarding systems against influence operations, disinformation campaigns, and large-scale cyberattacks.