My best advice is to be very upfront about the fact that
1.) You found some relations in your data that were not apart of your original hypotheses you were interested in testing.
2.) These results relations were still interesting enough to share, although the evidence should be taken with a grain of salt.
Because these relations were found spuriously, the evidence is not as strong as if they were the original hypotheses of interest. When writing this in your results, it's important to reflect this.
In my opinion (as a PhD in statistics, for what that's worth), I'd include unadjusted p-values and confidence intervals, and label them as such; "p-value (without adjusting for data exploration): 0.0013". Thus the reader isn't in the dark about your interesting discovery, but also is not misled about the strength of the evidence.
On a pragmatic note, note that this means this previously unhypothesized finding alone is unlikely to be sufficient for publication, as one could make the argument that the strength of evidence for this finding is not particularly strong. But hitching this result onto the published paper seems quite reasonable if that connection has the potential to be interesting other researchers in the field. One of my professors referred to this type of exploratory data analysis as "hypothesis generating" rather than "hypothesis testing".