Brand impersonation: Chase bank with credential phishing indicators

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

This rule checks for messages with or without attachments leveraging the Chase logo, and LinkAnalysis or Natural Language Understanding(NLU) has flagged credential phishing with medium to high confidence. The rule also excludes messages where all links are Chase affiliates, in addition to negating high trust sender root domains.

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
attachments (collection)
body
body.current_thread
body.links (collection)
headers.auth_summary
sender.email
type

Rule body MQL

type.inbound
and (
  (
    length(attachments) <= 3
    and any(attachments,
            .file_type in $file_types_images
            and any(ml.logo_detect(.).brands, .name == "Chase")
    )
  )
  or (
    length(attachments) == 0
    and any(ml.logo_detect(file.message_screenshot()).brands, .name == "Chase")
  )
)
and 0 < length(body.links) < 10
and (
  any(body.links,
      any([ml.link_analysis(.)],
          .credphish.disposition == "phishing"
          and .credphish.brand.confidence in ("medium", "high")
      )
  )
  or any(ml.nlu_classifier(body.current_thread.text).intents,
         .name in ("cred_theft") and .confidence in ("medium", "high")
  )
)
and not all(body.links,
            .href_url.domain.root_domain in (
              "chasecdn.com",
              "chase.com",
              "chase.co.uk",
              "gslbjpmchase.com",
              "jpmorganchase.com",
              "jpmorgan.com",
              "jpmorganfunds.com",
              "jpmprivatebank.com",
              "paymentech.com"
            )
)

// negate highly trusted sender domains unless they fail DMARC authentication
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
)
and (
  not profile.by_sender().solicited
  or profile.by_sender().any_messages_malicious_or_spam
)

Detection logic

Scope: inbound message.

inbound message
any of:
- all of:
  - length(attachments) ≤ 3
  - any of attachments where all hold:
    
    .file_type in $file_types_images
    any of ml.logo_detect(.).brands where:
    
    .name is 'Chase'
- all of:
  - length(attachments) is 0
  - any of ml.logo_detect(file.message_screenshot()).brands where:
    
    .name is 'Chase'
all of:
- length(body.links) > 0
- length(body.links) < 10
any of:
- any of body.links where:
  - any of [ml.link_analysis(.)] where all hold:
    
    .credphish.disposition is 'phishing'
    .credphish.brand.confidence in ('medium', 'high')
- any of ml.nlu_classifier(body.current_thread.text).intents where all hold:
  - .name in ('cred_theft')
  - .confidence in ('medium', 'high')
not:
- all of body.links where:
  - .href_url.domain.root_domain in ('chasecdn.com', 'chase.com', 'chase.co.uk', 'gslbjpmchase.com', 'jpmorganchase.com', 'jpmorgan.com', 'jpmorganfunds.com', 'jpmprivatebank.com', 'paymentech.com')
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
any of:
- not:
  - profile.by_sender().solicited
- profile.by_sender().any_messages_malicious_or_spam

Inspects: attachments[].file_type, body.current_thread.text, body.links, body.links[].href_url.domain.root_domain, headers.auth_summary.dmarc.pass, sender.email.domain.root_domain, type.inbound. Sensors: file.message_screenshot, ml.link_analysis, ml.logo_detect, ml.nlu_classifier, profile.by_sender. Reference lists: $file_types_images, $high_trust_sender_root_domains.

Indicators matched (17)

Field	Match	Value
`ml.logo_detect(attachments[]).brands[].name`	equals	`Chase`
`ml.logo_detect(file.message_screenshot()).brands[].name`	equals	`Chase`
`[ml.link_analysis(body.links[])][].credphish.disposition`	equals	`phishing`
`[ml.link_analysis(body.links[])][].credphish.brand.confidence`	member	`medium`
`[ml.link_analysis(body.links[])][].credphish.brand.confidence`	member	`high`
`ml.nlu_classifier(body.current_thread.text).intents[].name`	member	`cred_theft`
`ml.nlu_classifier(body.current_thread.text).intents[].confidence`	member	`medium`
`ml.nlu_classifier(body.current_thread.text).intents[].confidence`	member	`high`
`body.links[].href_url.domain.root_domain`	member	`chasecdn.com`
`body.links[].href_url.domain.root_domain`	member	`chase.com`
`body.links[].href_url.domain.root_domain`	member	`chase.co.uk`
`body.links[].href_url.domain.root_domain`	member	`gslbjpmchase.com`

5 more

`body.links[].href_url.domain.root_domain`	member	`jpmorganchase.com`
`body.links[].href_url.domain.root_domain`	member	`jpmorgan.com`
`body.links[].href_url.domain.root_domain`	member	`jpmorganfunds.com`
`body.links[].href_url.domain.root_domain`	member	`jpmprivatebank.com`
`body.links[].href_url.domain.root_domain`	member	`paymentech.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)