Operational Threat Modeling of Adversarial Disturbances in Continuous-Variable Quantum Communication

Continuous-variable quantum communication (CVQC) relies on finite-window estimation of phase space moments, making receiver decisions sensitive to finite measurement resolution, calibration uncertainty, and confidence-calibrated tolerances. This paper develops a receiver-centric threat modeling framework for structured (including adversarial) physical-layer disturbances under finite-sample inference. We introduce an operational taxonomy, reconnaissance, exploratory, and denial-of-service, defined by statistical visibility relative to acceptance regions rather than by assumed physical mechanisms. Using an effective estimator space Gaussian model r^′=Gr^+ξ with additive covariance N, we show how distinct mechanisms can be observationally equivalent within finite tolerances and we propose a protocol-agnostic scalar severity coordinate ΔE based on the covariance trace. We derive χ2-based missed-detection expressions and a soft detectability boundary scaling as 1/n, and we corroborate the predicted Pmiss(ν) behavior via Monte Carlo simulations across representative block sizes. The resulting framework clarifies the delimitation from conventional CV-QKD excess noise parameterization and provides a structured basis for monitoring-layer design and comparative threat-taxonomy mapping.