Medium Severity
Suspected Lookalike domain with suspicious language
Description
This rule identifies messages where links use typosquatting or lookalike domains similar to the sender domain, with at least one domain being either unregistered or recently registered (≤90 days). The messages must also contain indicators of business email compromise (BEC), credential theft, or abusive language patterns like financial terms or polite phrasing such as kindly. This layered approach targets phishing attempts combining domain deception with manipulative content
References
No references.
Sublime Security
Created Dec 24th, 2024 • Last updated Dec 24th, 2024
Feed Source
Sublime Core Feed
Source
type.inbound
// levenshtein distance (edit distance) between the SLD of the link and the sender domain is greater than 0 and less than or equal to 2.
// This detects typosquatting or domains that are deceptively similar to the sender.
and any(body.links,
length(.href_url.domain.sld) > 3
and 0 < strings.levenshtein(.href_url.domain.sld,
sender.email.domain.sld
) <= 2
//exclude onmicrosoft.com
and not sender.email.domain.root_domain == "onmicrosoft.com"
and (
// domains are not registered or registered within 90d
// network.whois(.href_url.domain).found == false
network.whois(.href_url.domain).days_old <= 90
or network.whois(sender.email.domain).found == false
or network.whois(sender.email.domain).days_old <= 90
)
)
// the mesasge is intent is BEC or Cred Theft, or is talking about financial invoicing/banking language, or a request contains "kindly"
and any(ml.nlu_classifier(body.current_thread.text).intents,
.name in ("bec", "cred_theft")
or any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "financial"
and (
.text in ("invoice", "banking information")
or .name == "request" and strings.icontains(.text, "kindly")
)
)
)
Playground
Test against your own EMLs or sample data.