Ahh thanks for the link and sorry for the snark; the finite universe optimization is cool! [0]

  # Why is CRLite able to compress so much data?
  
  Bloom filters are probabilistic data structures with an error rate due to data collisions. However, if you know the whole range of data that might be tested against the filter, you can compute all the false positives and build another layer to resolve those. Then you keep going until there are no more false positives. In practice, this happens in 25 to 30 layers, which results in substantial compression.

EDIT: Is there any risk of filter blow up (think 1000's of layers) if a CA did a mass revocation (maybe some root key leak)?

[0] https://github.com/mozilla/crlite/wiki#why-is-crlite-able-to...