Cross-Cloud Password Spray detection

Severity: medium
Time window: 1m
Group by: AuthenticationRequirement, ClientAppUsed, ConditionalAccessStatus, IPAddress, OperationName, RiskDetail, UserAgent, UserPrincipalName
Source: github.com/Azure/Azure-Sentinel

'This detection focuses on identifying potential cross-cloud brute force / Password Spray attempts involving Azure and AWS platforms. It monitors sign-in activities within the Azure Portal and AWS ConsoleLogins where brute force attempts are successful on both platforms in a synchronized manner.'

MITRE ATT&CK coverage

Tactic	Techniques
Credential Access	`T1110` Brute Force

Rules detecting the same action

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

AWS Console Login (Panther)
AWS Console Login Failed During MFA Challenge (Splunk)
AWS ConsoleLogin Failed Authentication (Sigma)
AWS CreateLoginProfile (Splunk)
AWS Credential Access Failed Login (Splunk)
AWS High Number Of Failed Authentications For User (Splunk)
AWS High Number Of Failed Authentications From Ip (Splunk)
AWS Multiple Failed MFA Requests For User (Splunk)

Rule body kusto

id: 1f40ed57-f54b-462f-906a-ac3a89cc90d4
name: Cross-Cloud Password Spray detection
description: |
  'This detection focuses on identifying potential cross-cloud brute force / Password Spray attempts involving Azure and AWS platforms. It monitors sign-in activities within the Azure Portal and AWS ConsoleLogins where brute force attempts are successful on both platforms in a synchronized manner.'
severity: Medium
requiredDataConnectors:
  - connectorId: AWS
    dataTypes:
      - AWSCloudTrail
  - connectorId: AzureActiveDirectory
    dataTypes:
      - SigninLogs
  - connectorId: BehaviorAnalytics
    dataTypes:
      - IdentityInfo
  - connectorId: MicrosoftThreatProtection
    dataTypes:
      - SecurityAlert
queryFrequency: 1d
queryPeriod: 1d
triggerOperator: gt
triggerThreshold: 0
tactics:
  - CredentialAccess
relevantTechniques:
  - T1110
query: |
  // Materialize a table named "Azure_Bruforce" containing Azure Portal sign-in logs within the last 1 day
  let Azure_Bruforce =  materialize (
      SigninLogs
  // Filter sign-in logs related to the Azure Portal
        | where AppDisplayName == "Azure Portal"
  // Exclude entries with empty OriginalRequestId
      | where isnotempty(OriginalRequestId)
  // Summarize various counts and sets based on brute force criteria
      | summarize 
        AzureSuccessfulEvent = countif(ResultType == 0), 
        AzureFailedEvent = countif(ResultType != 0), 
        totalAzureLoginEventId = dcount(OriginalRequestId), 
        AzureFailedEventsCount = dcountif(OriginalRequestId, ResultType != 0), 
        AzureSuccessfuleventsCount = dcountif(OriginalRequestId, ResultType == 0),
        AzureSetOfFailedevents = makeset(iff(ResultType != 0, OriginalRequestId, ""), 5), 
        AzureSetOfSuccessfulEvents = makeset(iff(ResultType == 0, OriginalRequestId, ""), 5) 
        by 
        IPAddress, 
        UserPrincipalName, 
        bin(TimeGenerated, 1min), 
        UserAgent,
        ConditionalAccessStatus,
        OperationName,
        RiskDetail,
        AuthenticationRequirement,
        ClientAppUsed
  // Extracting the name and UPN suffix from UserPrincipalName
      | extend
          Name = tostring(split(UserPrincipalName, '@')[0]),
          UPNSuffix = tostring(split(UserPrincipalName, '@')[1]));
  // Materialize a table named "AWS_Bruforce" containing AWS CloudTrail events related to ConsoleLogins within the last 1 day
  let AWS_Bruforce = materialize (
      AWSCloudTrail 
  // Filter CloudTrail events related to ConsoleLogin
      | where EventName == "ConsoleLogin" 
  // Extract ActionType from ResponseElements JSON
      | extend ActionType = tostring(parse_json(ResponseElements).ConsoleLogin)  
  // Summarize various counts and sets based on  brute force criteria 
      | summarize 
          AWSSuccessful=countif(ActionType == "Success"), 
          AWSFailed = countif(ActionType == "Failure"), 
          totalAwsEventId= dcount(AwsEventId), 
          AWSFailedEventsCount = dcountif(AwsEventId, ActionType == "Failure"), 
          AWSSuccessfuleventsCount = dcountif(AwsEventId, ActionType == "Success"), 
          AWSFailedevents = makeset(iff(ActionType == "Failure", AwsEventId, ""), 5), 
          AWSSuccessfulEvents = makeset(iff(ActionType == "Success", AwsEventId, ""), 5)  
  // Grouping by various attributes
          by 
          SourceIpAddress, 
          UserIdentityUserName,
          bin(TimeGenerated, 1min), 
          UserAgent );
  // Joining the Azure_Bruforce and AWS_Bruforce tables on matching IP addresses and UserAgents
  Azure_Bruforce
  | join kind=inner AWS_Bruforce on $left.IPAddress == $right.SourceIpAddress and $left.UserAgent == $right.UserAgent
  // Filtering based on conditions for failed and successful events
  | where (AWSFailedEventsCount >= 4 and AzureFailedEventsCount >= 5) and ((AzureSuccessfuleventsCount >= 1 and AzureFailedEvent > AzureSuccessfulEvent) or (AWSSuccessfuleventsCount >= 1 and AWSFailedEventsCount > AWSSuccessfuleventsCount))
entityMappings:
  - entityType: Account
    fieldMappings:
      - identifier: FullName
        columnName: UserPrincipalName
      - identifier: Name
        columnName: Name
      - identifier: UPNSuffix
        columnName: UPNSuffix
  - entityType: IP
    fieldMappings:
      - identifier: Address
        columnName: SourceIpAddress
customDetails:
   AwsUser: UserIdentityUserName
   UserAgent: UserAgent
   AzureUser: UserPrincipalName
   AzureClientAppUsed: ClientAppUsed
kind: Scheduled 
version: 1.0.1

Stages and Predicates

Let binding: `AWS_Bruforce`

let AWS_Bruforce = materialize (
    AWSCloudTrail 
    | where EventName == "ConsoleLogin" 
    | extend ActionType = tostring(parse_json(ResponseElements).ConsoleLogin)  
    | summarize 
        AWSSuccessful=countif(ActionType == "Success"), 
        AWSFailed = countif(ActionType == "Failure"), 
        totalAwsEventId= dcount(AwsEventId), 
        AWSFailedEventsCount = dcountif(AwsEventId, ActionType == "Failure"), 
        AWSSuccessfuleventsCount = dcountif(AwsEventId, ActionType == "Success"), 
        AWSFailedevents = makeset(iff(ActionType == "Failure", AwsEventId, ""), 5), 
        AWSSuccessfulEvents = makeset(iff(ActionType == "Success", AwsEventId, ""), 5)  
        by 
        SourceIpAddress, 
        UserIdentityUserName,
        bin(TimeGenerated, 1min), 
        UserAgent );

The stages below define let Azure_Bruforce (the rule's main pipeline source).

Stage 1: `source`

SigninLogs

Stage 2: `where`

| where AppDisplayName == "Azure Portal"

Stage 3: `where`

| where isnotempty(OriginalRequestId)

Stage 4: `summarize`

| summarize 
      AzureSuccessfulEvent = countif(ResultType == 0), 
      AzureFailedEvent = countif(ResultType != 0), 
      totalAzureLoginEventId = dcount(OriginalRequestId), 
      AzureFailedEventsCount = dcountif(OriginalRequestId, ResultType != 0), 
      AzureSuccessfuleventsCount = dcountif(OriginalRequestId, ResultType == 0),
      AzureSetOfFailedevents = makeset(iff(ResultType != 0, OriginalRequestId, ""), 5), 
      AzureSetOfSuccessfulEvents = makeset(iff(ResultType == 0, OriginalRequestId, ""), 5) 
      by 
      IPAddress, 
      UserPrincipalName, 
      bin(TimeGenerated, 1min), 
      UserAgent,
      ConditionalAccessStatus,
      OperationName,
      RiskDetail,
      AuthenticationRequirement,
      ClientAppUsed

Threshold: ge 5

Stage 5: `extend`

| extend
        Name = tostring(split(UserPrincipalName, '@')[0]),
        UPNSuffix = tostring(split(UserPrincipalName, '@')[1])

The stages below run on Azure_Bruforce (the outer pipeline).

Stage 6: `join`

Azure_Bruforce
| join kind=inner AWS_Bruforce on $left.IPAddress == $right.SourceIpAddress and $left.UserAgent == $right.UserAgent

Stage 7: `where`

| where (AWSFailedEventsCount >= 4 and AzureFailedEventsCount >= 5) and ((AzureSuccessfuleventsCount >= 1 and AzureFailedEvent > AzureSuccessfulEvent) or (AWSSuccessfuleventsCount >= 1 and AWSFailedEventsCount > AWSSuccessfuleventsCount))

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
`AWSFailedEventsCount`	ge	`4` transforms: `cased`
`AWSFailedEventsCount`	gt	`AWSSuccessfuleventsCount` transforms: `cased`
`AWSSuccessfuleventsCount`	ge	`1` transforms: `cased`
`AppDisplayName`	eq	`Azure Portal` transforms: `cased`
`AzureFailedEvent`	gt	`AzureSuccessfulEvent` transforms: `cased`
`AzureFailedEventsCount`	ge	`5` transforms: `cased`
`AzureSuccessfuleventsCount`	ge	`1` transforms: `cased`
`EventName`	eq	`ConsoleLogin` transforms: `cased`
`OriginalRequestId`	is_not_null	(no value, null check)

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
`AuthenticationRequirement`	`summarize`
`AzureFailedEvent`	`summarize`
`AzureFailedEventsCount`	`summarize`
`AzureSetOfFailedevents`	`summarize`
`AzureSetOfSuccessfulEvents`	`summarize`
`AzureSuccessfulEvent`	`summarize`
`AzureSuccessfuleventsCount`	`summarize`
`ClientAppUsed`	`summarize`
`ConditionalAccessStatus`	`summarize`
`IPAddress`	`summarize`
`OperationName`	`summarize`
`RiskDetail`	`summarize`
`UserAgent`	`summarize`
`UserPrincipalName`	`summarize`
`totalAzureLoginEventId`	`summarize`
`Name`	`extend`
`UPNSuffix`	`extend`

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`d` / `u`	Half-page down / up
`gg` / `G`	Top / bottom
`h` / `l`	History back / forward
`f`	Follow link (`Shift` = new tab)
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`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)

Cross-Cloud Password Spray detection

MITRE ATT&CK coverage

Rules detecting the same action

Rule body kusto

Stages and Predicates

Let binding: `AWS_Bruforce`

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `summarize`

Stage 5: `extend`

Stage 6: `join`

Stage 7: `where`

Indicators

Output fields

Keyboard shortcuts

Search operators

Cross-Cloud Password Spray detection

MITRE ATT&CK coverage

Rules detecting the same action

Rule body kusto

Stages and Predicates

Let binding: AWS_Bruforce

Stage 1: source

Stage 2: where

Stage 3: where

Stage 4: summarize

Stage 5: extend

Stage 6: join

Stage 7: where

Indicators

Output fields

Let binding: `AWS_Bruforce`

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `summarize`

Stage 5: `extend`

Stage 6: `join`

Stage 7: `where`