Brand impersonation: Amazon Web Services (AWS)

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

Detects messages impersonating AWS through similar display names combined with security-themed content and authentication failures. Excludes legitimate AWS communications and trusted senders.

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 regex.icontains(strings.replace_confusables(sender.display_name),
                    '\baws\b|amazon web services|\bses\b'
)
and (
  // ML Topic Analysis and Credential Theft Detection
  any(ml.nlu_classifier(body.current_thread.text).topics,
      .name in ("Security and Authentication", "Secure Message")
      and .confidence == "high"
  )
  or any(ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).topics,
         .name in ("Security and Authentication", "Secure Message")
         and .confidence == "high"
         and beta.ocr(file.message_screenshot()).text != ""
  )
  or any(ml.nlu_classifier(body.current_thread.text).intents,
         .name == "cred_theft" and .confidence == "high"
  )
  or any(ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).intents,
         .name == "cred_theft" and .confidence == "high"
  )
)
// Not from legitimate AWS domains
// there was a DMARC check here, but a lot of users send AWS notifications to groups/mailing lists that breaks DMARC
and not (
  sender.email.domain.root_domain in $org_domains
  or sender.email.domain.root_domain in (
    "amazon.com",
    "amazonaws.com",
    "amazonses.com",
    "awsevents.com",
    "aws-experience.com",
    "marketplace.aws",
    "aws.com",
    "amazonaws.cn",
    "repost.aws",
    "awscustomercouncil.com",
    "airtableemail.com", // used for re:Invent
    "nmls.org", // "state examination system", realtor software
    "mktgcampaigns.com", // Elastic + AWS co-marketing emails
    "awseducate.com",
    "awsacademy.com"
  )
  or sender.email.domain.tld == "local"
)
// 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

Detection logic

Scope: inbound message.

Detects messages impersonating AWS through similar display names combined with security-themed content and authentication failures. Excludes legitimate AWS communications and trusted senders.

inbound message
strings.replace_confusables(sender.display_name) matches '\\baws\\b|amazon web services|\\bses\\b'
any of:
- any of ml.nlu_classifier(body.current_thread.text).topics where all hold:
  - .name in ('Security and Authentication', 'Secure Message')
  - .confidence is 'high'
- any of ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).topics where all hold:
  - .name in ('Security and Authentication', 'Secure Message')
  - .confidence is 'high'
  - beta.ocr(file.message_screenshot()).text is not ''
- any of ml.nlu_classifier(body.current_thread.text).intents where all hold:
  - .name is 'cred_theft'
  - .confidence is 'high'
- any of ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).intents where all hold:
  - .name is 'cred_theft'
  - .confidence is 'high'
none of:
- sender.email.domain.root_domain in $org_domains
- sender.email.domain.root_domain in ('amazon.com', 'amazonaws.com', 'amazonses.com', 'awsevents.com', 'aws-experience.com', 'marketplace.aws', 'aws.com', 'amazonaws.cn', 'repost.aws', 'awscustomercouncil.com', 'airtableemail.com', 'nmls.org', 'mktgcampaigns.com', 'awseducate.com', 'awsacademy.com')
- sender.email.domain.tld is 'local'
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
not:
- profile.by_sender().solicited

Inspects: body.current_thread.text, headers.auth_summary.dmarc.pass, sender.display_name, sender.email.domain.root_domain, sender.email.domain.tld, type.inbound. Sensors: beta.ocr, file.message_screenshot, ml.nlu_classifier, profile.by_sender, regex.icontains, strings.replace_confusables. Reference lists: $high_trust_sender_root_domains, $org_domains.

Indicators matched (27)

Field	Match	Value
`regex.icontains`	regex	`\baws\b\|amazon web services\|\bses\b`
`ml.nlu_classifier(body.current_thread.text).topics[].name`	member	`Security and Authentication`
`ml.nlu_classifier(body.current_thread.text).topics[].name`	member	`Secure Message`
`ml.nlu_classifier(body.current_thread.text).topics[].confidence`	equals	`high`
`ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).topics[].name`	member	`Security and Authentication`
`ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).topics[].name`	member	`Secure Message`
`ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).topics[].confidence`	equals	`high`
`ml.nlu_classifier(body.current_thread.text).intents[].name`	equals	`cred_theft`
`ml.nlu_classifier(body.current_thread.text).intents[].confidence`	equals	`high`
`ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).intents[].name`	equals	`cred_theft`
`ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).intents[].confidence`	equals	`high`
`sender.email.domain.root_domain`	member	`amazon.com`

15 more

`sender.email.domain.root_domain`	member	`amazonaws.com`
`sender.email.domain.root_domain`	member	`amazonses.com`
`sender.email.domain.root_domain`	member	`awsevents.com`
`sender.email.domain.root_domain`	member	`aws-experience.com`
`sender.email.domain.root_domain`	member	`marketplace.aws`
`sender.email.domain.root_domain`	member	`aws.com`
`sender.email.domain.root_domain`	member	`amazonaws.cn`
`sender.email.domain.root_domain`	member	`repost.aws`
`sender.email.domain.root_domain`	member	`awscustomercouncil.com`
`sender.email.domain.root_domain`	member	`airtableemail.com`
`sender.email.domain.root_domain`	member	`nmls.org`
`sender.email.domain.root_domain`	member	`mktgcampaigns.com`
`sender.email.domain.root_domain`	member	`awseducate.com`
`sender.email.domain.root_domain`	member	`awsacademy.com`
`sender.email.domain.tld`	equals	`local`

`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)