type.inbound
and (
strings.ilevenshtein(sender.display_name, 'finra') <= 1
or strings.ilevenshtein(sender.email.domain.sld, 'finra') <= 1
)
and any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "financial"
)
and length(ml.nlu_classifier(body.current_thread.text).intents) > 0
and sender.email.domain.root_domain not in~ (
'finra.org',
'finrax.com',
'finca.wine', // a wine company
'finta.com' // unrelated domain caught by levenshtein
)
and (
(
profile.by_sender().prevalence in ("new", "outlier")
and not profile.by_sender().solicited
)
or (
profile.by_sender().any_messages_malicious_or_spam
and not profile.by_sender().any_messages_benign
)
)
Playground
Test against your own EMLs or sample data.