Poisoned　search　results　are　misleading　people　to　download　invalid,　incorrect　or　even　nonexistent　resources　in　some　popular　file　sharing　systems.　In　order　to　estimate　effects　brought　by　those　poisoned　results,　a　dataset　about　3　million　items　were　gathered　from　Kad,　including　shared　resources＇　hash　values　along　with　related　metadata.　We　analyzed　the　amount　of　poisoned　results　based　on　the　dataset,　and　revealed　zipf-like　distributions　between　number　of　names　and　the　number　of　hash　values.　Besides,　we　evaluated　the　indirect　effects　of　poisoned　search　results　through　the　dissimilarities　among　names　of　different　hash　values　having　same　metadata.　The　analysis　shows　that,　based　on　our　dataset,　audios　are　the　most　shared　but　least　poisoned　indirectly,　videos　are　the　most　poisoned　directly　and　indirectly,　and　other　types　are　indirectly　poisoned　almost　at　the　same　level.　©　2011　IEEE.