Configurable software systems, such as software product lines, enable the generation of diverse software configurations tailored to specific requirements by combining reusable features. A key challenge in product lines lies in combinatorial interaction testing, which ensures that all possible feature combinations are tested to identify configurations that may fail. When a configuration fails, pinpointing the exact feature or feature interaction causing the error is crucial. However, error masking - where faulty interactions remain undetected because other features or interactions could override their effects - poses an obstacle in product-line testing. Despite its critical implications, error masking in product lines has received limited attention in existing research. To address this gap, we investigate and analyze on already identified errors of the real-world product line JHipster and quantitatively analyze these errors in terms of masking. In our case study, we find evidence of the existence of error masking in JHipster and how the detectability of masked errors is influenced. For one feature-interaction error in JHipster, we only can identify 82.4% of all configurations containing this error due to masking effects. By analyzing masked errors of a real-world product line, we raise awareness of investigating feature-interaction masking further in software product lines.