The electrochemical impedance spectra (EIS) of tethered bilayer membranes (tBLMs) were analyzed, and the analytical solution for the spectral response of membranes containing natural or artificially introduced defects was derived. The analysis carried out in this work shows that the EIS features of an individual membrane defect cannot be modeled by conventional electrical elements. The primary reason for this is the complex nature of impedance of the submembrane ionic reservoir separating the phospholipid layer and the solid support. We demonstrate that its EIS response, in the case of radially symmetric defects, is described by the Hankel functions of a complex variable. Therefore, neither the impedance of the submembrane reservoir nor the total impedance of tBLMs can be modeled using the conventional elements of the equivalent electrical circuits of interfaces. There are, however, some limiting cases in which the complexity of the EIS response of the submembrane space reduces. In the high frequency limit, the EIS response of a submembrane space that surrounds the defect transforms into a response of a constant phase element (CPE) with the exponent (alpha) value of 0.5. The onset of this transformation is, beside other parameters, dependent on the defect size. Large-sized defects push the frequency limit lower, therefore, the EIS spectra exhibiting CPE behavior with a approximate to 0.5, can serve as a diagnostic criterion for the presence of such defects. In the low frequency limit, the response is dependent on the density of the defects, and it transforms into the capacitive impedance if the area occupied by a defect is finite. The higher the defect density, the higher the frequency edge at which the onset of the capacitive behavior is observed. Consequently, the presented analysis provides practical tools to evaluate the defect density in tBLMs, which could be utilized in tBLM-based biosensor applications. Alternatively, if the parameters of the defects, e.g., ion channels, such as the diameter and the conductance are known, the EIS data analysis provides a possibility to estimate other physical parameters of the system, such as thickness of the submembrane reservoir and its conductance. Finally, current analysis demonstrates a possibility to discriminate between the situations, in which the membrane defects are evenly distributed or clustered on the surface of tBLMs. Such sensitivity of EIS could be used for elucidation of the mechanisms of interaction between the proteins and the membranes.