Potential Kerberoasting

Severity: medium
Time window: 1d
Group by: ClientIPAddress, Computer, Status, TargetDomainName, TargetUserName, TicketEncryptionType, TicketOptions
Author: Microsoft Security Research
Source: github.com/Azure/Azure-Sentinel

A service principal name (SPN) is used to uniquely identify a service instance in a Windows environment. Each SPN is usually associated with a service account. Organizations may have used service accounts with weak passwords in their environment. An attacker can try requesting Kerberos ticket-granting service (TGS) service tickets for any SPN from a domain controller (DC) which contains a hash of the Service account. This can then be used for offline cracking. This hunting query looks for accounts that are generating excessive requests to different resources within the last hour compared with the previous 24 hours. Normal users would not make an unusually large number of request within a small time window. This is based on 4769 events which can be very noisy so environment based tweaking might be needed.

MITRE ATT&CK coverage

Tactic	Techniques
Credential Access	`T1558` Steal or Forge Kerberos Tickets

Event coverage

Provider	Event	Title
Security-Auditing	Event ID 4769	A Kerberos service ticket was requested.

Rule body kusto

id: 1572e66b-20a7-4012-9ec4-77ec4b101bc8
name: Potential Kerberoasting
description: |
  'A service principal name (SPN) is used to uniquely identify a service instance in a Windows environment.
  Each SPN is usually associated with a service account. Organizations may have used service accounts with weak passwords in their environment.
  An attacker can try requesting Kerberos ticket-granting service (TGS) service tickets for any SPN from a domain controller (DC) which contains a hash of the Service account. This can then be used for offline cracking.
  This hunting query looks for accounts that are generating excessive requests to different resources within the last hour compared with the previous 24 hours.  Normal users would not make an unusually large number of request within a small time window. This is based on 4769 events which can be very noisy so environment based tweaking might be needed.'
severity: Medium
requiredDataConnectors:
  - connectorId: SecurityEvents
    dataTypes:
      - SecurityEvent
  - connectorId: WindowsSecurityEvents
    dataTypes:
      - SecurityEvent
  - connectorId: WindowsForwardedEvents
    dataTypes:
      - WindowsEvent
queryFrequency: 1h
queryPeriod: 1d
triggerOperator: gt
triggerThreshold: 0
tactics:
  - CredentialAccess
relevantTechniques:
  - T1558
query: |
  let starttime = 1d;
  let endtime = 1h;
  let prev23hThreshold = 4;
  let prev1hThreshold = 15;
  let Kerbevent = (union isfuzzy=true
  (SecurityEvent
  | where TimeGenerated >= ago(starttime)
  | where EventID == 4769
  | parse EventData with * 'TicketEncryptionType">' TicketEncryptionType "<" *
  | where TicketEncryptionType == '0x17'
  | parse EventData with * 'TicketOptions">' TicketOptions "<" *
  | where TicketOptions == '0x40810000'
  | parse EventData with * 'Status">' Status "<" *
  | where Status == '0x0'
  | parse EventData with * 'ServiceName">' ServiceName "<" *
  | where ServiceName !contains "$" and ServiceName !contains "krbtgt"
  | parse EventData with * 'TargetUserName">' TargetUserName "<" *
  | where TargetUserName !contains "$@" and TargetUserName !contains ServiceName
  | parse EventData with * 'IpAddress">::ffff:' ClientIPAddress "<" *
  ),
  (
  WindowsEvent
  | where TimeGenerated >= ago(starttime)
  | where EventID == 4769 and EventData has '0x17' and EventData has '0x40810000' and EventData has 'krbtgt'
  | extend TicketEncryptionType = tostring(EventData.TicketEncryptionType)
  | where TicketEncryptionType == '0x17'
  | extend TicketOptions = tostring(EventData.TicketOptions)
  | where TicketOptions == '0x40810000'
  | extend Status = tostring(EventData.Status)
  | where Status == '0x0'
  | extend ServiceName = tostring(EventData.ServiceName)
  | where ServiceName !contains "$" and ServiceName !contains "krbtgt"
  | extend TargetUserName = tostring(EventData.TargetUserName)
  | where TargetUserName !contains "$@" and TargetUserName !contains ServiceName
  | extend ClientIPAddress = tostring(EventData.IpAddress)
  ));
  let Kerbevent23h = Kerbevent
  | where TimeGenerated >= ago(starttime) and TimeGenerated < ago(endtime)
  | summarize ServiceNameCountPrev23h = dcount(ServiceName), ServiceNameSet23h = makeset(ServiceName)
  by Computer, TargetUserName,TargetDomainName, ClientIPAddress, TicketOptions, TicketEncryptionType, Status
  | where ServiceNameCountPrev23h < prev23hThreshold;
  let Kerbevent1h =
  Kerbevent
  | where TimeGenerated >= ago(endtime)
  | summarize min(TimeGenerated), max(TimeGenerated), ServiceNameCountPrev1h = dcount(ServiceName), ServiceNameSet1h = makeset(ServiceName)
  by Computer, TargetUserName, TargetDomainName, ClientIPAddress, TicketOptions, TicketEncryptionType, Status;
  Kerbevent1h
  | join kind=leftanti
  (
  Kerbevent23h
  ) on TargetUserName, TargetDomainName
  // Threshold value set above is based on testing, this value may need to be changed for your environment.
  | where ServiceNameCountPrev1h > prev1hThreshold
  | project StartTime = min_TimeGenerated, EndTime = max_TimeGenerated, TargetUserName, Computer, ClientIPAddress, TicketOptions,
  TicketEncryptionType, Status, ServiceNameCountPrev1h, ServiceNameSet1h, TargetDomainName
  | extend HostName = tostring(split(Computer, ".")[0]), DomainIndex = toint(indexof(Computer, '.'))
  | extend HostNameDomain = iff(DomainIndex != -1, substring(Computer, DomainIndex + 1), Computer)
  | extend TargetAccount = strcat(TargetDomainName,  "\\", TargetUserName)
  | project-away DomainIndex
entityMappings:
  - entityType: Account
    fieldMappings:
      - identifier: FullName
        columnName: TargetAccount
      - identifier: Name
        columnName: TargetUserName
      - identifier: NTDomain
        columnName: TargetDomainName
  - entityType: Host
    fieldMappings:
      - identifier: FullName
        columnName: Computer
      - identifier: HostName
        columnName: HostName
      - identifier: DnsDomain
        columnName: HostNameDomain
  - entityType: IP
    fieldMappings:
      - identifier: Address
        columnName: ClientIPAddress
version: 1.1.7
kind: Scheduled
metadata:
    source:
        kind: Community
    author:
        name: Microsoft Security Research
    support:
        tier: Community
    categories:
        domains: [ "Security - Others", "Identity" ]

Stages and Predicates

Parameters

let starttime = 1d;
let endtime = 1h;
let prev23hThreshold = 4;
let prev1hThreshold = 15;

Let binding: `Kerbevent23h`

let Kerbevent23h = Kerbevent
| where TimeGenerated >= ago(starttime) and TimeGenerated < ago(endtime)
| summarize ServiceNameCountPrev23h = dcount(ServiceName), ServiceNameSet23h = makeset(ServiceName)
by Computer, TargetUserName,TargetDomainName, ClientIPAddress, TicketOptions, TicketEncryptionType, Status
| where ServiceNameCountPrev23h < prev23hThreshold;

Derived from starttime, endtime, prev23hThreshold, Kerbevent.

The stages below define let Kerbevent1h (the rule's main pipeline source).

Stage 1: `source`

let Kerbevent

Stage 2: `source`

let Kerbevent23h

Stage 3: `source`

let Kerbevent1h

Stage 4: `union`

union isfuzzy=true

Stage 5: `source`

SecurityEvent

Stage 6: `where`

| where TimeGenerated >= ago(starttime)

The stages below run on Kerbevent1h (the outer pipeline).

Stage 7: `where`

Kerbevent1h
| where EventID == 4769

Stage 8: `parse`

| parse EventData with * 'TicketEncryptionType">' TicketEncryptionType "<" *

Stage 9: `where`

| where TicketEncryptionType == '0x17'

Stage 10: `parse`

| parse EventData with * 'TicketOptions">' TicketOptions "<" *

Stage 11: `where`

| where TicketOptions == '0x40810000'

Stage 12: `parse`

| parse EventData with * 'Status">' Status "<" *

Stage 13: `where`

| where Status == '0x0'

Stage 14: `parse`

| parse EventData with * 'ServiceName">' ServiceName "<" *

Stage 15: `where`

| where ServiceName !contains "$" and ServiceName !contains "krbtgt"

Stage 16: `parse`

| parse EventData with * 'TargetUserName">' TargetUserName "<" *

Stage 17: `where`

| where TargetUserName !contains "$@" and TargetUserName !contains ServiceName

Stage 18: `parse`

| parse EventData with * 'IpAddress">::ffff:' ClientIPAddress "<" *

Stage 19: `source`

WindowsEvent

Stage 20: `where`

| where TimeGenerated >= ago(starttime)

Stage 21: `where`

| where EventID == 4769 and EventData has '0x17' and EventData has '0x40810000' and EventData has 'krbtgt'

Stage 22: `extend`

| extend TicketEncryptionType = tostring(EventData.TicketEncryptionType)

Stage 23: `where`

| where TicketEncryptionType == '0x17'

Stage 24: `extend`

| extend TicketOptions = tostring(EventData.TicketOptions)

Stage 25: `where`

| where TicketOptions == '0x40810000'

Stage 26: `extend`

| extend Status = tostring(EventData.Status)

Stage 27: `where`

| where Status == '0x0'

Stage 28: `extend`

| extend ServiceName = tostring(EventData.ServiceName)

Stage 29: `where`

| where ServiceName !contains "$" and ServiceName !contains "krbtgt"

Stage 30: `extend`

| extend TargetUserName = tostring(EventData.TargetUserName)

Stage 31: `where`

| where TargetUserName !contains "$@" and TargetUserName !contains ServiceName

Stage 32: `extend`

| extend ClientIPAddress = tostring(EventData.IpAddress)

Stage 33: `where`

| where TimeGenerated >= ago(endtime)

Stage 34: `summarize`

| summarize min(TimeGenerated), max(TimeGenerated), ServiceNameCountPrev1h = dcount(ServiceName), ServiceNameSet1h = makeset(ServiceName)
by Computer, TargetUserName, TargetDomainName, ClientIPAddress, TicketOptions, TicketEncryptionType, Status

Threshold: gt 15

Stage 35: `join` (negated)

| join kind=leftanti
(
Kerbevent23h
) on TargetUserName, TargetDomainName

Stage 36: `where`

| where ServiceNameCountPrev1h > prev1hThreshold

Stage 37: `project`

| project StartTime = min_TimeGenerated, EndTime = max_TimeGenerated, TargetUserName, Computer, ClientIPAddress, TicketOptions,
TicketEncryptionType, Status, ServiceNameCountPrev1h, ServiceNameSet1h, TargetDomainName

Stage 38: `extend` (3 consecutive steps)

| extend HostName = tostring(split(Computer, ".")[0]), DomainIndex = toint(indexof(Computer, '.'))
| extend HostNameDomain = iff(DomainIndex != -1, substring(Computer, DomainIndex + 1), Computer)
| extend TargetAccount = strcat(TargetDomainName,  "\\", TargetUserName)

Stage 39: `project-away`

| project-away DomainIndex

Exclusions

Top-level NOT(...) conjuncts: predicates this rule actively suppresses.

Field	Kind	Excluded values
`ServiceName`	contains	`$`
`ServiceName`	contains	`krbtgt`
`TargetUserName`	contains	`$@`
`TargetUserName`	contains	`ServiceName`
`ServiceName`	contains	`$`
`ServiceName`	contains	`krbtgt`
`TargetUserName`	contains	`$@`
`TargetUserName`	contains	`ServiceName`
`EventData`	match	`0x17`
`EventData`	match	`0x40810000`
`EventData`	match	`krbtgt`
`EventID`	eq	`4769`
`ServiceNameCountPrev23h`	lt	`4`
`Status`	eq	`0x0`
`TicketEncryptionType`	eq	`0x17`
`TicketOptions`	eq	`0x40810000`

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
`EventData`	match	`0x17` transforms: `term` `0x40810000` transforms: `term` `krbtgt` transforms: `term`
`EventID`	eq	`4769` transforms: `cased` corpus 10 (splunk 6, kusto 4)
`ServiceName`	contains	`$` `krbtgt`
`ServiceNameCountPrev1h`	gt	`15` transforms: `cased`
`Status`	eq	`0x0` transforms: `cased` corpus 3 (kusto 2, sigma 1)
`TargetUserName`	contains	`$@` `ServiceName`
`TicketEncryptionType`	eq	`0x17` transforms: `cased` corpus 8 (splunk 4, sigma 3, kusto 1)
`TicketOptions`	eq	`0x40810000` transforms: `cased` corpus 4 (splunk 2, sigma 1, kusto 1)

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
`ClientIPAddress`	`project`
`Computer`	`project`
`EndTime`	`project`
`ServiceNameCountPrev1h`	`project`
`ServiceNameSet1h`	`project`
`StartTime`	`project`
`Status`	`project`
`TargetDomainName`	`project`
`TargetUserName`	`project`
`TicketEncryptionType`	`project`
`TicketOptions`	`project`
`HostName`	`extend`
`HostNameDomain`	`extend`
`TargetAccount`	`extend`

`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)

Potential Kerberoasting

MITRE ATT&CK coverage

Event coverage

Rule body kusto

Stages and Predicates

Parameters

Let binding: Kerbevent23h

Stage 1: source

Stage 2: source

Stage 3: source

Stage 4: union

Stage 5: source

Stage 6: where

Stage 7: where

Stage 8: parse

Stage 9: where

Stage 10: parse

Stage 11: where

Stage 12: parse

Stage 13: where

Stage 14: parse

Stage 15: where

Stage 16: parse

Stage 17: where

Stage 18: parse

Stage 19: source

Stage 20: where

Stage 21: where

Stage 22: extend

Stage 23: where

Stage 24: extend

Stage 25: where

Stage 26: extend

Stage 27: where

Stage 28: extend

Stage 29: where

Stage 30: extend

Stage 31: where

Stage 32: extend

Stage 33: where

Stage 34: summarize

Stage 35: join (negated)

Stage 36: where

Stage 37: project

Stage 38: extend (3 consecutive steps)

Stage 39: project-away