Possibly but no one has demonstrated them, and there are probably many fewer in Zero than in previous AlphaGos. Previously AlphaGos suffered from problems which Silver calls 'delusions' (https://www.reddit.com/r/MachineLearning/comments/76xjb5/ama...) ie persistent long-term misevaluations of specific board positions, which were however (entirely? how would we know if not?) fixed by Zero's self-play - arguably these are not 'adversarial examples' in the sense you're thinking of but then I'm not sure what would constitute an adversarial example for a Go agent, so maybe the AlphaGo 'delusions' were the equivalent.

(On a side note, the more I think about Anthony et al 2017/AlphaGo Zero's tree/expert iteration, the more beautifully simple it appears to me.)