K-means sensitivity to outliers?
yes, in detecting abnormal cases.

In the k-means based outlier detection technique, the data are partitioned into k groups by assigning them to the closest cluster centers.

Once assigned we can compute the distance or dissimilarity between each object and its cluster center, and pick those with largest distances as outliers.

k-means clustering for Outlier detection