Natural circulation is employed in new designs of light water reactors to enhance passive safety by maintaining flow and heat removal without pumps. Under low-pressure and low-flow-rate conditions, natural circulation is susceptible to two-phase instabilities leading to undesirable flow oscillations and operational difficulties. Flashing instability is one of the most widely reported low-pressure natural circulation instabilities, related to saturated vaporization triggered by a hydrostatic pressure drop in an adiabatic riser above a heated section. While existing studies have reported flashing instability experiments, modeling, and simulations including successes in matching numerical results and experimental data, solid yet clear analytical explanations for many of its qualitative features are still rare. To enhance the physical understanding beyond stability boundary prediction, the current work develops, validates, and analyzes a linear stability model of flashing instability. This model adopts a one-dimensional Drift-Flux Model simplified by physical assumptions and approximations, and it includes optional component models to match an actual facility for validation. Stability tests are performed on a 5-m-tall natural circulation loop, providing comprehensive benchmark data covering stability boundaries, one-dimensional transient signals, and periodic mean waveforms from local measurements. Validation confirms acceptable predictions of steady states, stability boundaries, and oscillation periods. The tractable model formulation leads to a closed-form characteristic function facilitating analytical manipulations and physical interpretations, based on which dominant pressure drop responses to inlet flow rate are extracted. The major instability mechanism is identified as a strong response of the two-phase driving force to the inlet flow rate that is delayed by enthalpy transportation through a long single-phase distance and can become an overwhelmingly destabilizing positive feedback under low-frequency perturbations. Experimentally reported qualitative features, including stability changes, timescale relations, and oscillation patterns, are analytically predicted and physically explained with clarity. In general, this study enriches experimental resources of flashing instability with a comprehensive dataset and provides a simple yet realistic analytical basis for physically understanding flashing instability beyond predicting stability boundaries.