In Tibetan, as words are written consecutively without delimiters, finding unknown word boundary is difficult. This paper presents a hybrid approach for Tibetan unknown word identification for offline corpus processing. Firstly, Tibetan named entity is preprocessed based on natural annotation. Secondly, other Tibetan unknown words are extracted from word segmentation fragments using MTC, the combination of a statistical metric and a set of context sensitive rules. In addition, the preliminary experimental results on Tibetan News Corpus are reported. Lexicon-based Tibetan word segmentation system SegT with proposed unknown word extension mechanism is indeed helpful to promote the performance of Tibetan word segmentation. It increases the F-score of Tibetan word segmentation by 4.15% on random-selected test set. Our unknown word identification scheme can find new words in any length and in any field.