Neuroscientists and cyber threat actors operate on a "black box" paradigm, relying on both the passive measurement of physical exhaust to infer hidden internal states, and the active injection of targeted stimuli to disrupt or manipulate those systems. This paper introduces the Neuro-Cyber Exploitation and Reconnaissance Taxonomy (NeuroCERT), a theoretical framework that maps cybersecurity side-channel attacks and active vectors to psychophysiological measurement and neurostimulation techniques. It proposes that AI can serve as a translational layer to parse noisy biological data into actionable metrics or automate closed-loop attacks, suggesting the potential of novel threat vectors in human-centric cybersecurity.