We'll describe our analysis of open Opal Data, commissioned by Transport NSW. The data treatment used two main methods: first, it broke up trips and journeys and exposed only the total tap-on and tap-off counts at each place and time, with some removal or aggregation of some rare events. Second, it applied a version of Differential Privacy to the totals. We show that it is possible to extract the Differential Privacy parameters, which is not in itself a problem, but rather a further reason for those parameters to be public in the first place. Second, we show that the presence or absence of commuters can be inferred with some (small) probability in some cases.