Robots have been playing an increasingly important role in human life, but their performance is yet far from perfection. Based on extant literature in interpersonal, organizational, and human-machine communication, the current study develops a three-fold categorization of technical failures (i.e., logic, semantic, and syntax failures) commonly observed in human-robot interactions from the interactants’ end, investigating it together with four trust repair strategies: internal-attribution apology, external-attribution apology, denial, and no repair. The 743 observations conducted through an online experiment reveals there exist some nuances in participants’ perceived division between competence- and integrity-based trust violations, given the ontological differences between humans and machines. The findings also suggest prior propositions about trust repair from the perspective of attribution theory only explain part of the variance, in addition to some significant main effects of failure types and repair methods on HRI-based trust.