The rapid pace of cybersecurity-related technology emergence, diffusion, adoption, and obsolescence means that numerous tools developed for forecasting technological change are all but inapplicable. With the change in the geopolitical environment towards a multipolar competition, where offensive operations in the cyber-space are commonplace, forecasting cyber technologies is becoming vital to modern states. In this work, we formalize the innovation in cybersecurity technologies as an evolutionary process in the Gillespie-Orr Fitness Landscapes evolution model with attention - the Attentioned Fitness Landscapes Model (AFLM). We show that empirically derived features of innovation processes, such as S-curves and Hype Curves, naturally arise from this formalization and can be used to evaluate scenarios of geopolitical change. This opens avenues for their derivation from first principles, potentially allowing for earlier forecasting.