Advance Fee Fraud (AFF) from freemail provider or suspicious TLD

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

Advance Fee Fraud (AFF) is a type of BEC/Fraud involving upfront fees for promised future returns, such as lottery scams, inheritance payouts, and investment opportunities. This rule identifies messages from Freemail domains or suspicious TLDS, including those with suspicious reply-to addresses. It utilizes Natural Language Understanding to detect AFF language in their contents.

Threat classification

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

Category	Values
Attack types	BEC/Fraud
Tactics and techniques	Social engineering

Event coverage

Message attribute
body
body.current_thread
body.html
body.links (collection)
headers (collection)
headers.reply_to (collection)
recipients
sender.email
subject
type

Rule body MQL

type.inbound
and (
  sender.email.domain.domain in $free_email_providers
  or (
    length(headers.reply_to) > 0
    and all(headers.reply_to,
            (
              .email.domain.root_domain in $free_email_providers
              or .email.domain.tld in $suspicious_tlds
              or (
                network.whois(.email.domain).days_old < 365
                and length(coalesce(body.html.raw, "")) == 0
              )
            )
            and .email.email != sender.email.email
    )
  )
  or sender.email.domain.tld in $suspicious_tlds
  or any(["jp", "jo"], strings.iends_with(sender.email.domain.tld, .))
  or (
    length(recipients.to) == 0
    and any(headers.reply_to,
            .email.domain.root_domain != sender.email.domain.root_domain
    )
  )
)
and (
  any(ml.nlu_classifier(body.current_thread.text).intents,
      .name == "advance_fee" and .confidence in ("medium", "high")
  )
  or (
    length(body.current_thread.text) < 200
    and regex.icontains(body.current_thread.text,
                        '(?:donation|inheritence|\$\d,\d{3}\,\d{3}|lottery)'
    )
    and not regex.icontains(body.current_thread.text,
                            '(?:closed.{0,50})?\$\d,\d{3}\,\d{3}.{0,100}(?:homes|realty|sale)?'
    )
    and not any(body.links,
                regex.icontains(.href_url.url,
                                '(?:donation|inheritence|\$\d,\d{3}\,\d{3}|lottery)'
                )
    )
    and (
      (
        (length(headers.references) > 0 or headers.in_reply_to is null)
        and not (
          (
            strings.istarts_with(subject.subject, "RE:")
            // out of office auto-reply
            or strings.istarts_with(subject.subject, "Automatic reply:")
            or strings.istarts_with(subject.subject, "R:")
            or strings.istarts_with(subject.subject, "ODG:")
            or strings.istarts_with(subject.subject, "答复:")
            or strings.istarts_with(subject.subject, "AW:")
            or strings.istarts_with(subject.subject, "TR:")
            or strings.istarts_with(subject.subject, "FWD:")
            or regex.icontains(subject.subject,
                               '^(\[[^\]]+\]\s?){0,3}(re|fwd?)\s?:'
            )
          )
        )
      )
      or any(headers.reply_to, .email.email != sender.email.email)
    )
  )
)
and (
  not profile.by_sender().solicited
  or profile.by_sender().any_messages_malicious_or_spam
)
and not profile.by_sender().any_messages_benign

Detection logic

Scope: inbound message.

inbound message
any of:
- sender.email.domain.domain in $free_email_providers
- all of:
  - length(headers.reply_to) > 0
  - all of headers.reply_to where all hold:
    
    any of:
    
    .email.domain.root_domain in $free_email_providers
    .email.domain.tld in $suspicious_tlds
    all of:
    
    network.whois(.email.domain).days_old < 365
    length(coalesce(body.html.raw, '')) is 0
    .email.email is not sender.email.email
- sender.email.domain.tld in $suspicious_tlds
- any of ['jp', 'jo'] where:
  - strings.iends_with(sender.email.domain.tld)
- all of:
  - length(recipients.to) is 0
  - any of headers.reply_to where:
    
    .email.domain.root_domain is not sender.email.domain.root_domain
any of:
- any of ml.nlu_classifier(body.current_thread.text).intents where all hold:
  - .name is 'advance_fee'
  - .confidence in ('medium', 'high')
- all of:
  - length(body.current_thread.text) < 200
  - body.current_thread.text matches '(?:donation|inheritence|\\$\\d,\\d{3}\\,\\d{3}|lottery)'
  - not:
    
    body.current_thread.text matches '(?:closed.{0,50})?\\$\\d,\\d{3}\\,\\d{3}.{0,100}(?:homes|realty|sale)?'
  - not:
    
    any of body.links where:
    
    .href_url.url matches '(?:donation|inheritence|\\$\\d,\\d{3}\\,\\d{3}|lottery)'
  - any of:
    
    all of:
    
    any of:
    
    length(headers.references) > 0
    headers.in_reply_to is missing
    none of:
    
    subject.subject starts with 'RE:'
    subject.subject starts with 'Automatic reply:'
    subject.subject starts with 'R:'
    subject.subject starts with 'ODG:'
    subject.subject starts with '答复:'
    subject.subject starts with 'AW:'
    subject.subject starts with 'TR:'
    subject.subject starts with 'FWD:'
    subject.subject matches '^(\\[[^\\]]+\\]\\s?){0,3}(re|fwd?)\\s?:'
    any of headers.reply_to where:
    
    .email.email is not sender.email.email
any of:
- not:
  - profile.by_sender().solicited
- profile.by_sender().any_messages_malicious_or_spam
not:
- profile.by_sender().any_messages_benign

Inspects: body.current_thread.text, body.html.raw, body.links, body.links[].href_url.url, headers.in_reply_to, headers.references, headers.reply_to, headers.reply_to[].email.domain, headers.reply_to[].email.domain.root_domain, headers.reply_to[].email.domain.tld, headers.reply_to[].email.email, recipients.to, sender.email.domain.domain, sender.email.domain.root_domain, sender.email.domain.tld, sender.email.email, subject.subject, type.inbound. Sensors: ml.nlu_classifier, network.whois, profile.by_sender, regex.icontains, strings.iends_with, strings.istarts_with. Reference lists: $free_email_providers, $suspicious_tlds.

Indicators matched (14)

Field	Match	Value
`ml.nlu_classifier(body.current_thread.text).intents[].name`	equals	`advance_fee`
`ml.nlu_classifier(body.current_thread.text).intents[].confidence`	member	`medium`
`ml.nlu_classifier(body.current_thread.text).intents[].confidence`	member	`high`
`regex.icontains`	regex	`(?:donation\|inheritence\|\$\d,\d{3}\,\d{3}\|lottery)`
`regex.icontains`	regex	`(?:closed.{0,50})?\$\d,\d{3}\,\d{3}.{0,100}(?:homes\|realty\|sale)?`
`strings.istarts_with`	prefix	`RE:`
`strings.istarts_with`	prefix	`Automatic reply:`
`strings.istarts_with`	prefix	`R:`
`strings.istarts_with`	prefix	`ODG:`
`strings.istarts_with`	prefix	`答复:`
`strings.istarts_with`	prefix	`AW:`
`strings.istarts_with`	prefix	`TR:`

2 more

`strings.istarts_with`	prefix	`FWD:`
`regex.icontains`	regex	`^(\[[^\]]+\]\s?){0,3}(re\|fwd?)\s?:`

`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)