Energy-efficient idling of computers has a substantial influence on their lifetime energy consumption, total cost of ownership, and environmental impact. Mechanisms to reduce power consumption during idle rely on complex operating-system support, an area that is prone to regressions. Idle-power regressions are challenging to identify, even when actively looking for them: In-band measurements can easily perturb the monitored idle states. Additionally, as the idle power strongly depends on frequency and duration of interruptions, statistically sound comparisons require long observation periods. In this paper, we present a measurement-based approach to pinpoint regressions in the Linux kernel that degrade the energy efficiency of idle systems. For that, we design an out-of-band measurement infrastructure that avoids the probe effect. Our approach based on bisection can isolate the culprit of regressions across a large number of code changes. We discuss the critical role of classification and present approaches to strengthen its reliability. Finally, we demonstrate our approach on a newly discovered power regression, as well as a known reference case by reliably finding the responsible code change.