All-solid-state lithium-ion batteries (ASSBs) are expected to represent a future alternative compared to conventional lithium-ion batteries with liquid electrolytes (LIBs). The excellent performance of today's LIBs relies to a large extent on the development of liquid electrolytes that form stable, or at least slowly degrading, interfaces (interphases) with both anodes and cathodes. This has not yet been achieved in ASSBs, and degradation of anode and cathode interfaces of solid electrolytes (SE) is one of the key issues to be solved. Unlike investigations of liquid/solid interfaces, the degradation of interfaces between the solid electrodes and the SE is challenging since (i) solid/solid interfaces are less easily accessed analytically, (ii) interface compounds may contribute only in very low concentrations to spectroscopic or spectrometric data, and (iii) a high spatial resolution is required to determine the local component distribution. Typically, solid/solid interface investigations are primarily based on electrochemical experiments, diffraction studies, electron microscopy, or on theoretical calculations to obtain sufficient information. Interestingly, the prospects of recent advanced analytical tools such as time-of-flight secondary-ion mass spectrometry (ToF-SIMS) are not fully exploited yet; therefore, we demonstrate in this paper that ToF-SIMS can provide valuable insights into the interphase composition and microstructure of ASSBs. For this purpose, we combine local compositional information from ToF-SIMS and complementary X-ray photoelectron spectroscopy measurements to characterize and visualize the degradation mechanism in the LiNi0.6Co0.2Mn0.2O2/Li6PS5Cl-composite cathode of an ASSB. Our results indicate that sulfates and phosphates play an important role in the formation of a solid electrolyte interface (SEI), whereas transition-metal chlorides, phosphides, and sulfides can be neglected. Furthermore, to the best of our knowledge, we show for the first time the local structure and morphology of the SEI layer on the basis of information about the chemical composition using ToF-SIMS analysis.