BEC with unusual reply-to or return-path mismatch

Severity: high
Type: rule
Source: github.com/sublime-security/sublime-rules

Detects an unusual header mismatch where the sender is not a freemail address, but the reply-to or return-path are. NLU also detects a BEC intent with medium or high confidence.

Threat classification

Sublime's own taxonomy (not MITRE ATT&CK).

Category	Values
Attack types	BEC/Fraud
Tactics and techniques	Evasion, Free email provider, Social engineering

Event coverage

Message attribute
body.current_thread
headers (collection)
headers.auth_summary
headers.hops (collection)
headers.reply_to (collection)
headers.return_path
sender
sender.email
type

Rule body MQL

type.inbound
and any(ml.nlu_classifier(body.current_thread.text).intents,
        .name in ("bec", "advance_fee") and .confidence == "high"
)
and (
  headers.return_path.domain.root_domain in $free_email_providers
  or (
    length(headers.reply_to) > 0
    and all(headers.reply_to,
            .email.domain.root_domain in $free_email_providers
    )
  )
)
and (
  (
    sender.email.domain.root_domain == "paypal.com"
    and (
      not headers.auth_summary.dmarc.pass
      or headers.auth_summary.dmarc.pass is null
    )
  )
  or sender.email.domain.root_domain is null
  or sender.email.domain.root_domain != "paypal.com"
)
and sender.email.domain.root_domain not in $free_email_providers

// negate gmail autoforwards and null return paths
and (
  headers.return_path.email is null
  or not strings.ilike(headers.return_path.local_part, "*+caf_=*")
)

// negate listservs
and not (
  any(headers.hops, any(.fields, .name == "List-Unsubscribe"))
  and strings.contains(sender.display_name, "via")
)

// negate legit replies
and not (length(headers.references) > 0 or headers.in_reply_to is not null)

// legitimate quickbooks from known sender
and not (
  sender.email.email == "quickbooks@notification.intuit.com"
  and headers.auth_summary.spf.pass
  and beta.profile.by_reply_to().prevalence in (
    "outlier",
    "uncommon",
    "rare",
    "common"
  )
)

Detection logic

Scope: inbound message.

Detects an unusual header mismatch where the sender is not a freemail address, but the reply-to or return-path are. NLU also detects a BEC intent with medium or high confidence.

inbound message
any of ml.nlu_classifier(body.current_thread.text).intents where all hold:
- .name in ('bec', 'advance_fee')
- .confidence is 'high'
any of:
- headers.return_path.domain.root_domain in $free_email_providers
- all of:
  - length(headers.reply_to) > 0
  - all of headers.reply_to where:
    
    .email.domain.root_domain in $free_email_providers
any of:
- all of:
  - sender.email.domain.root_domain is 'paypal.com'
  - any of:
    
    not:
    
    headers.auth_summary.dmarc.pass
    headers.auth_summary.dmarc.pass is missing
- sender.email.domain.root_domain is missing
- sender.email.domain.root_domain is not 'paypal.com'
sender.email.domain.root_domain not in $free_email_providers
any of:
- headers.return_path.email is missing
- not:
  - headers.return_path.local_part matches '*+caf_=*'
not:
- all of:
  - any of headers.hops where:
    
    any of .fields where:
    
    .name is 'List-Unsubscribe'
  - sender.display_name contains 'via'
none of:
- length(headers.references) > 0
- headers.in_reply_to is set
not:
- all of:
  - sender.email.email is 'quickbooks@notification.intuit.com'
  - headers.auth_summary.spf.pass
  - beta.profile.by_reply_to().prevalence in ('outlier', 'uncommon', 'rare', 'common')

Inspects: body.current_thread.text, headers.auth_summary.dmarc.pass, headers.auth_summary.spf.pass, headers.hops, headers.hops[].fields, headers.hops[].fields[].name, headers.in_reply_to, headers.references, headers.reply_to, headers.reply_to[].email.domain.root_domain, headers.return_path.domain.root_domain, headers.return_path.email, headers.return_path.local_part, sender.display_name, sender.email.domain.root_domain, sender.email.email, type.inbound. Sensors: beta.profile.by_reply_to, ml.nlu_classifier, strings.contains, strings.ilike. Reference lists: $free_email_providers.

Indicators matched (8)

Field	Match	Value
`ml.nlu_classifier(body.current_thread.text).intents[].name`	member	`bec`
`ml.nlu_classifier(body.current_thread.text).intents[].name`	member	`advance_fee`
`ml.nlu_classifier(body.current_thread.text).intents[].confidence`	equals	`high`
`sender.email.domain.root_domain`	equals	`paypal.com`
`strings.ilike`	substring	`+caf_=`
`headers.hops[].fields[].name`	equals	`List-Unsubscribe`
`strings.contains`	substring	`via`
`sender.email.email`	equals	`quickbooks@notification.intuit.com`

`j` / `k`	Scroll down / up
`d` / `u`	Half-page down / up
`gg` / `G`	Top / bottom
`h` / `l`	History back / forward
`f`	Follow link (`Shift` = new tab)
`/`	Focus search
`?`	Toggle this help
`↑` / `↓`	Navigate search results
`Enter`	Open highlighted result
`Esc`	Close results / dialog

`type:`	`events` / `rules` / `providers`
`vendor:`	`sigma` / `elastic` / `splunk` / `kusto` / `chronicle` (vendor name alone also works: `sigma:`, `kql:`, `secops:`…)
`tactic:`	TA-id, slug, or name: `credential_access`, `TA0006`
`technique:`	technique or sub-technique ID: `T1003`, `T1003.001` (alias `tech:`)
`severity:`	`critical` / `high` / `medium` / `low` / `informational` (alias `sev:`)
`risk_score`	Numeric comparison on the Elastic risk score (0 to 100): `risk_score>50`, `risk_score<=20`, `risk_score=99` (alias `risk`; Elastic rules only)
`stages:`	Rules with exactly N pipeline stages
`correlation:`	`single_event` / `sequence` / `alternatives` / `alternatives_cross_log` / `all_required` / `correlated`
`with:`	Co-occurrence event-id; stacks (`with:4624 with:4769`) to require all, while a comma list in one occurrence (`with:4624,4769`) is an either-or group. Implies multi-event
`like:`	Structural neighbors of a rule slug (equivalents + subsumption stricter / broader): `like:comsvcs_lsass_memory_dump-splunk-sysmon`
`groupby:`	Entity-grouping substring match against `group_by_keys`: `groupby:user`, `groupby:host`
`uses:`	Rules whose predicate tree touches the field (any kind, any value): `uses:CommandLine`
`excludes:`	Rules with top-level `not()` clauses on the field (FP whitelists): `excludes:ParentImage`
`field:` / `value:`	Predicate search; narrows rule cards to those with a matching leaf and drives the indicator tier. Unquoted = substring, wildcards allowed (`value:mimikatz`)
`indicator:`	Shorthand for `field:F value:V`: `indicator:Image=*\powershell.exe`
`kind:`	Filter by predicate kind. Narrows rule cards to those carrying a matching predicate leaf (`vendor:elastic kind:cidr_match`) and drives the indicator tier: `contains` / `starts_with` / `ends_with` / `regex` / `cidr` / `eq` / `in` … (operator aliases `op:`/`match:`)
`has:` / `no:`	`sample`, `field`, `notes`, `refs`, `trace`, `thirdparty`, `rule`, `pattern`, `timewindow`, `threshold`, `newterms`, `sigma`/`elastic`/`splunk`/`kusto`/`chronicle`
`-op:val`	Exclude matches; works on most operators but not `type:`/`like:`/`has:`/`no:` (use `no:<flag>` to exclude a rule flag): `tactic:execution -vendor:splunk`. Standalone `-kind:`/`-field:`/`-value:` drop every rule carrying a matching predicate leaf (`type:rules -kind:is_null`)
`field:"…"` / `value:"…"`	Quoted value = anchored exact match (also allows spaces): `value:"net user"`
`a,b`	Comma = OR inside one operator (`vendor:sigma,elastic`, `severity:high,critical`); repeating a facet merges the same way. `field:`/`value:` never split (literal commas)
`vendors:` / `stage:`	Singular and plural spellings fold to the canonical operator and value: `tactics:` = `tactic:`, `type:event` = `type:events`, `correlation:sequences` = `correlation:sequence`, `has:thresholds` = `has:threshold`
`"quoted phrase"`	Exact-match a multi-word phrase (free text)

BEC with unusual reply-to or return-path mismatch

Threat classification

Event coverage

Rule body MQL

Detection logic

Indicators matched (8)

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