Detection rules › Sublime MQL
Brand impersonation: United Healthcare
Detects messages impersonating United Healthcare (UHC) by analyzing display names that contain variations of 'United Healthcare' or 'UHC', including those with character substitutions. The rule excludes legitimate messages from verified UHC domains that pass DMARC authentication and handles high-trust sender domains appropriately.
Threat classification
Sublime's own taxonomy (not MITRE ATT&CK).
| Category | Values |
|---|---|
| Attack types | Credential Phishing |
| Tactics and techniques | Impersonation: Brand, Social engineering |
Event coverage
| Message attribute |
|---|
| body.current_thread |
| headers.auth_summary |
| sender |
| sender.email |
| type |
Rule body MQL
type.inbound
and (
// display name contains UHC
(
strings.ilike(strings.replace_confusables(sender.display_name),
'*united healthcare*'
)
or strings.ilike(strings.replace_confusables(sender.display_name), 'UHC*')
or regex.icontains(sender.display_name, 'united ?health ?care')
)
// levenshtein distance similar to UHC
or strings.ilevenshtein(strings.replace_confusables(sender.display_name),
'united healthcare'
) <= 1
or (
regex.icontains(body.current_thread.text, 'united ?health ?care')
and (
regex.icontains(body.current_thread.text, 'quick .{0,10}survey')
// Free benefits/items lure commonly used in UHC impersonation
or regex.icontains(body.current_thread.text,
'dental (benefits?|coverage).{0,50}(free|eligible|no.{0,10}cost)'
)
or regex.icontains(body.current_thread.text,
'free.{0,30}(toothbrush|dental|benefit)'
)
)
)
// Brand name in sender local part from non-UHC domain
or (
strings.icontains(sender.email.local_part, "unitedhealthcare")
and sender.email.domain.root_domain not in (
"uhc.com",
"unitedhealthcare.com",
"uhcmedicaresolutions.com",
"unitedhealthcareupdate.com",
"yourhealth-wellnessteam.com",
"uhc-customer.com",
"leavesource.com"
)
)
)
// and the sender is not in org_domains or from UHC domains and passes auth
and not (
sender.email.domain.root_domain in $org_domains
or (
(
sender.email.domain.root_domain in (
"uhc.com",
"unitedhealthcare.com",
"uhcmedicaresolutions.com",
"unitedhealthcareupdate.com",
"yourhealth-wellnessteam.com",
"uhc-customer.com",
"leavesource.com"
)
or sender.display_name in (
"UHCOM Faculty Affairs",
"UHC Construction Services"
)
)
and headers.auth_summary.dmarc.pass
)
)
// negate UHC job related posting
and not any(ml.nlu_classifier(body.current_thread.text).topics,
.name == "Professional and Career Development"
and .confidence == "high"
)
// and the sender is not from high trust sender root domains
and (
(
sender.email.domain.root_domain in $high_trust_sender_root_domains
and not headers.auth_summary.dmarc.pass
)
or sender.email.domain.root_domain not in $high_trust_sender_root_domains
)
Detection logic
Scope: inbound message.
Detects messages impersonating United Healthcare (UHC) by analyzing display names that contain variations of 'United Healthcare' or 'UHC', including those with character substitutions. The rule excludes legitimate messages from verified UHC domains that pass DMARC authentication and handles high-trust sender domains appropriately.
- inbound message
any of:
any of:
- strings.replace_confusables(sender.display_name) matches '*united healthcare*'
- strings.replace_confusables(sender.display_name) matches 'UHC*'
- sender.display_name matches 'united ?health ?care'
- strings.replace_confusables(sender.display_name) is similar to 'united healthcare'
all of:
- body.current_thread.text matches 'united ?health ?care'
any of:
- body.current_thread.text matches 'quick .{0,10}survey'
- body.current_thread.text matches 'dental (benefits?|coverage).{0,50}(free|eligible|no.{0,10}cost)'
- body.current_thread.text matches 'free.{0,30}(toothbrush|dental|benefit)'
all of:
- sender.email.local_part contains 'unitedhealthcare'
- sender.email.domain.root_domain not in ('uhc.com', 'unitedhealthcare.com', 'uhcmedicaresolutions.com', 'unitedhealthcareupdate.com', 'yourhealth-wellnessteam.com', 'uhc-customer.com', 'leavesource.com')
none of:
- sender.email.domain.root_domain in $org_domains
all of:
any of:
- sender.email.domain.root_domain in ('uhc.com', 'unitedhealthcare.com', 'uhcmedicaresolutions.com', 'unitedhealthcareupdate.com', 'yourhealth-wellnessteam.com', 'uhc-customer.com', 'leavesource.com')
- sender.display_name in ('UHCOM Faculty Affairs', 'UHC Construction Services')
- headers.auth_summary.dmarc.pass
not:
any of
ml.nlu_classifier(body.current_thread.text).topicswhere all hold:- .name is 'Professional and Career Development'
- .confidence is 'high'
any of:
all of:
- sender.email.domain.root_domain in $high_trust_sender_root_domains
not:
- headers.auth_summary.dmarc.pass
- sender.email.domain.root_domain not in $high_trust_sender_root_domains
Inspects: body.current_thread.text, headers.auth_summary.dmarc.pass, sender.display_name, sender.email.domain.root_domain, sender.email.local_part, type.inbound. Sensors: ml.nlu_classifier, regex.icontains, strings.icontains, strings.ilevenshtein, strings.ilike, strings.replace_confusables. Reference lists: $high_trust_sender_root_domains, $org_domains.
Indicators matched (19)
| Field | Match | Value |
|---|---|---|
strings.ilike | substring | *united healthcare* |
strings.ilike | substring | UHC* |
regex.icontains | regex | united ?health ?care |
strings.ilevenshtein | fuzzy | united healthcare |
regex.icontains | regex | quick .{0,10}survey |
regex.icontains | regex | dental (benefits?|coverage).{0,50}(free|eligible|no.{0,10}cost) |
regex.icontains | regex | free.{0,30}(toothbrush|dental|benefit) |
strings.icontains | substring | unitedhealthcare |
sender.email.domain.root_domain | member | uhc.com |
sender.email.domain.root_domain | member | unitedhealthcare.com |
sender.email.domain.root_domain | member | uhcmedicaresolutions.com |
sender.email.domain.root_domain | member | unitedhealthcareupdate.com |
7 more
sender.email.domain.root_domain | member | yourhealth-wellnessteam.com |
sender.email.domain.root_domain | member | uhc-customer.com |
sender.email.domain.root_domain | member | leavesource.com |
sender.display_name | member | UHCOM Faculty Affairs |
sender.display_name | member | UHC Construction Services |
ml.nlu_classifier(body.current_thread.text).topics[].name | equals | Professional and Career Development |
ml.nlu_classifier(body.current_thread.text).topics[].confidence | equals | high |