Okta Cleartext Passwords Extracted via SCIM Application

Severity: high
Log types: Okta.SystemLog
Reference: https://www.authomize.com/blog/authomize-discovers-password-stealing-and-impersonation-risks-to-in-okta/
Source: github.com/panther-labs/panther-analysis

An application admin has extracted cleartext user passwords via SCIM app. Malcious actors can extract plaintext passwords by creating a SCIM application under their control and configuring it to sync passwords from Okta.

MITRE ATT&CK coverage

Tactic	Techniques
Credential Access	`T1556` Modify Authentication Process

Rules detecting the same action

Other rules on this platform that filter on the same API call or operation.

Attempt to Modify an Okta Application (Elastic)
Okta Application Modified or Deleted (Sigma)
Okta Org2Org application created of modified (Panther)

Rule body yaml

AnalysisType: rule
Filename: okta_password_extraction_via_scim.py
RuleID: "Okta.Password.Extraction.via.SCIM"
DisplayName: "Okta Cleartext Passwords Extracted via SCIM Application"
Enabled: true
LogTypes:
  - Okta.SystemLog
Reports:
  MITRE ATT&CK:
    - TA0006:T1556 # Modify Authentication Process
Severity: High
Description: >
  An application admin has extracted cleartext user passwords via SCIM app.
  Malcious actors can extract plaintext passwords by creating a SCIM application under their control and configuring it to sync passwords from Okta.
Reference: >
  https://www.authomize.com/blog/authomize-discovers-password-stealing-and-impersonation-risks-to-in-okta/
DedupPeriodMinutes: 30
Threshold: 1
Tests:
  - ExpectedResult: false
    Log:
      actor:
        alternateId: homer.simpson@duff.com
        displayName: Homer Simpson
        id: 00abc123
        type: User
      authenticationcontext:
        authenticationStep: 0
        externalSessionId: 100-abc-9999
      client:
        device: Computer
        geographicalContext:
          city: Springfield
          country: United States
          geolocation:
            lat: 20
            lon: -25
          postalCode: "12345"
          state: Ohio
        ipAddress: 1.3.2.4
        userAgent:
          browser: CHROME
          os: Mac OS X
          rawUserAgent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.0.0 Safari/537.36
        zone: "null"
      debugcontext:
        debugData:
          requestId: AbCdEf12G
          requestUri: /api/v1/users/AbCdEfG/lifecycle/reset_factors
          url: /api/v1/users/AbCdEfG/lifecycle/reset_factors?
      displaymessage: Authentication of user via MFA
      eventtype: user.authentication.auth_via_mfa
      legacyeventtype: core.user.factor.attempt_fail
      outcome:
        result: SUCCESS
      published: "2022-06-22 18:18:29.015"
      request:
        ipChain:
          - geographicalContext:
              city: Springfield
              country: United States
              geolocation:
                lat: 20
                lon: -25
              postalCode: "12345"
              state: Ohio
            ip: 1.3.2.4
            version: V4
      securitycontext:
        asNumber: 701
        asOrg: verizon
        domain: verizon.net
        isProxy: false
        isp: verizon
      severity: INFO
      target:
        - alternateId: peter.griffin@company.com
          displayName: Peter Griffin
          id: 0002222AAAA
          type: User
      transaction:
        detail: {}
        id: ABcDeFgG
        type: WEB
      uuid: AbC-123-XyZ
      version: "0"
    Name: Other Event
  - ExpectedResult: true
    Log:
      actor:
        alternateId: homer.simpson@duff.com
        displayName: Homer Simpson
        id: 00abc123
        type: User
      authenticationcontext:
        authenticationStep: 0
        externalSessionId: 100-abc-9999
      client:
        device: Computer
        geographicalContext:
          city: Springfield
          country: United States
          geolocation:
            lat: 20
            lon: -25
          postalCode: "12345"
          state: Ohio
        ipAddress: 1.3.2.4
        userAgent:
          browser: CHROME
          os: Mac OS X
          rawUserAgent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.0.0 Safari/537.36
        zone: "null"
      debugcontext:
        debugData:
          requestId: AbCdEf12G
          requestUri: /api/v1/users/AbCdEfG/lifecycle/reset_factors
          url: /api/v1/users/AbCdEfG/lifecycle/reset_factors?
      displaymessage: Authentication of user via MFA
      eventtype: application.lifecycle.update
      legacyeventtype: core.user.factor.attempt_fail
      outcome:
        reason: Pushing user passwords
        result: SUCCESS
      published: "2022-06-22 18:18:29.015"
      request:
        ipChain:
          - geographicalContext:
              city: Springfield
              country: United States
              geolocation:
                lat: 20
                lon: -25
              postalCode: "12345"
              state: Ohio
            ip: 1.3.2.4
            version: V4
      securitycontext:
        asNumber: 701
        asOrg: verizon
        domain: verizon.net
        isProxy: false
        isp: verizon
      severity: INFO
      target:
        - alternateId: peter.griffin@company.com
          displayName: Peter Griffin
          id: 0002222AAAA
          type: User
      transaction:
        detail: {}
        id: ABcDeFgG
        type: WEB
      uuid: AbC-123-XyZ
      version: "0"
    Name: FastPass Phishing Block Event

Detection logic

Condition

eventType eq "application.lifecycle.update"
outcome.reason contains "Pushing user passwords"

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

Field	Kind	Values
`eventType`	eq	`application.lifecycle.update`
`outcome.reason`	contains	`Pushing user passwords`

Output fields

Fields the rule emits when it matches. Chronicle authors list these in the outcome block; they appear on the detection and $risk_score drives alerting. Sentinel / Defender XDR rules build them up through project / summarize / extend stages. Sentinel maps these into alert fields via entityMappings and customDetails; Defender XDR custom detections surface them as alert fields directly.

Field	Source
`event_type`	`eventtype`
`severity`
`actor`
`client`
`request`
`outcome`
`target`
`debug_context`	`debugcontext`
`authentication_context`	`authenticationcontext`
`security_context`	`securitycontext`
`ips`	`p_any_ip_addresses`
`displayName`	`actor.displayName`
`alternateId`	`actor.alternateId`
`alternateId`	`target.alternateId`

`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)