DNA barcoding using the nuclear internal transcribed spacer (ITS) has become prevalent in surveys of fungal diversity. This approach is, however, associated with numerous caveats, including the desire for speed, rather than accuracy, through the use of automated analytical pipelines, and the shortcomings of reference sequence repositories. Here we use the case of a specimen of the bracket fungus Trametes s.lat. (which includes the common and widespread turkey tail, T. versicolor) to illustrate these problems. The material was collected in Vietnam as part of a biodiversity inventory including DNA barcoding approaches for arthropods, plants and fungi. The ITS barcoding sequence of the query taxon was compared against reference sequences in GenBank and the curated fungal ITS database UNITE, using BLASTn and MegaBLAST, and was subsequently analysed in a multiple alignment-based phylogenetic context through a maximum likelihood tree including related sequences. Our results initially indicated issues with BLAST searches, including the use of Frairwise local alignments and sorting through Total score and E value, rather than Percentage identity, as major shortcomings of the DNA barcoding approach. However, after thorough analysis of the results, we concluded that the single most important problem of this approach was incorrect sequence labelling, calling for the implementation of third-party annotations or analogous approaches in primary sequence repositories. In addition, this particular example revealed problems of improper fungal nomenclature, which required reinstatement of the genus name Cubamyces (= Leioirametes), with three new combinations: C. flavidus, C lactineus and C. menziesii. The latter was revealed as the correct identification of the query taxon, although the name did not appear among the best BLAST hits. While the best BLAST hits did correspond to the target taxon in terms of sequence data, their label names were misleading or unresolved, including [Fungal endophyte], [Uncultured fungus], Basidiomycota, Trametes cf. cubensis, Lenzites elegans and Geotrichum candidum (an unrelated ascomycetous contaminant). Our study demonstrates that accurate identification of fungi through molecular barcoding is currently not a fast-track approach that can be achieved through automated pipelines.