Detect Potential Kerberoast Activities

Status: available
Severity: medium
Time window: 2m
Group by: AccountSid, AccountUpn, DeviceName
Source: github.com/Azure/Azure-Sentinel

This query aim to detect if someone requests service tickets (where count => maxcount) The query requires trimming to set a baseline level for MaxCount
Mitre Technique: Kerberoasting (T1558.003) @MattiasBorg82

MITRE ATT&CK coverage

Tactic	Techniques
Credential Access	`T1558.003` Steal or Forge Kerberos Tickets: Kerberoasting

Rule body kusto

id: 12134de5-361b-427c-a1a0-d43f40a593c4
name: Detect Potential Kerberoast Activities
description: |
  This query aim to detect if someone requests service tickets (where count => maxcount)
  The query requires trimming to set a baseline level for MaxCount  
  Mitre Technique: Kerberoasting (T1558.003)
  @MattiasBorg82
severity: Medium
status: Available
requiredDataConnectors:
  - connectorId: MicrosoftThreatProtection
    dataTypes:
      - IdentityLogonEvents
queryFrequency: 1h
queryPeriod: 1h
triggerOperator: gt
triggerThreshold: 0
tactics:
  - CredentialAccess
relevantTechniques:
  - T1558.003
tag:
  - Kerberoast
query: |
  let MaxCount = 70; //Number of requests per 2 minute timeframe, depending on org size.
  IdentityLogonEvents
  | where ActionType == "LogonSuccess"
  | where Protocol == "Kerberos"
  | extend json = todynamic(parse_json(tostring(AdditionalFields)))
  | extend SPN = json.Spns,
         AttackTechniques = json.AttackTechniques
        | project-away json
  | where isnotempty(SPN)
  | where AttackTechniques has "T1558.003"
  | mv-expand SPN
          | extend SPNType = tostring(extract(@"^\w+",0,tostring(SPN)))
  | distinct tostring(SPN), DeviceName, AccountUpn, AccountSid, bin(TimeGenerated, 2m), ReportId, tostring(AttackTechniques)
  | summarize count(), SPNS=(make_list(SPN, 100000)),ReportId=tostring((make_list(ReportId, 100000))[0]) by AccountUpn,AccountSid,DeviceName, bin(TimeGenerated, 2m), tostring(AttackTechniques)
  | extend SPNS = (replace_regex(tostring(SPNS), @'[^\w+-\/]+', '')) 
  | where count_ >= MaxCount
  | extend HostName = iff(DeviceName has '.', substring(DeviceName, 0, indexof(DeviceName, '.')), DeviceName)
  | extend DnsDomain = iff(DeviceName has '.', substring(DeviceName, indexof(DeviceName, '.') + 1), "")
  | extend AccountDomain = tostring(split(AccountUpn, '@')[1]), AccountName = tostring(split(AccountUpn, '@')[0])
entityMappings:
  - entityType: Host
    fieldMappings:
      - identifier: FullName
        columnName: DeviceName
      - identifier: HostName
        columnName: HostName
      - identifier: DnsDomain
        columnName: DnsDomain
  - entityType: Account
    fieldMappings:
      - identifier: FullName
        columnName: AccountUpn
      - identifier: DnsDomain
        columnName: AccountDomain
      - identifier: Name
        columnName: AccountName
version: 1.0.0
kind: Scheduled

Stages and Predicates

Parameters

let MaxCount = 70;

Stage 1: `source`

IdentityLogonEvents

Stage 2: `where`

| where ActionType == "LogonSuccess"

Stage 3: `where`

| where Protocol == "Kerberos"

Stage 4: `extend`

| extend json = todynamic(parse_json(tostring(AdditionalFields)))

Stage 5: `extend`

| extend SPN = json.Spns,
       AttackTechniques = json.AttackTechniques

Stage 6: `project-away`

| project-away json

Stage 7: `where`

| where isnotempty(SPN)

Stage 8: `where`

| where AttackTechniques has "T1558.003"

Stage 9: `mv-expand`

| mv-expand SPN

Stage 10: `extend`

| extend SPNType = tostring(extract(@"^\w+",0,tostring(SPN)))

Stage 11: `distinct`

| distinct tostring(SPN), DeviceName, AccountUpn, AccountSid, bin(TimeGenerated, 2m), ReportId, tostring(AttackTechniques)

Stage 12: `summarize`

| summarize count(), SPNS=(make_list(SPN, 100000)),ReportId=tostring((make_list(ReportId, 100000))[0]) by AccountUpn,AccountSid,DeviceName, bin(TimeGenerated, 2m), tostring(AttackTechniques)

Stage 13: `extend`

| extend SPNS = (replace_regex(tostring(SPNS), @'[^\w+-\/]+', ''))

Stage 14: `where`

| where count_ >= MaxCount

Stage 15: `extend` (3 consecutive steps)

| extend HostName = iff(DeviceName has '.', substring(DeviceName, 0, indexof(DeviceName, '.')), DeviceName)
| extend DnsDomain = iff(DeviceName has '.', substring(DeviceName, indexof(DeviceName, '.') + 1), "")
| extend AccountDomain = tostring(split(AccountUpn, '@')[1]), AccountName = tostring(split(AccountUpn, '@')[0])

HostName =

ifDeviceName has "."substring(DeviceName, 0, indexof(DeviceName, '.'))

elseDeviceName

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
`ActionType`	eq	`LogonSuccess` transforms: `cased` corpus 5 (kusto 5)
`AttackTechniques`	match	`T1558.003` transforms: `term`
`Protocol`	eq	`Kerberos` transforms: `cased` corpus 3 (kusto 3)
`SPN`	is_not_null	(no value, null check)
`count_`	ge	`70` transforms: `cased`

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
`AccountSid`	`summarize`
`AccountUpn`	`summarize`
`DeviceName`	`summarize`
`ReportId`	`summarize`
`SPNS`	`extend`
`HostName`	`extend`
`DnsDomain`	`extend`
`AccountDomain`	`extend`
`AccountName`	`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)

Detect Potential Kerberoast Activities

MITRE ATT&CK coverage

Rule body kusto

Stages and Predicates

Parameters

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `extend`

Stage 5: `extend`

Stage 6: `project-away`

Stage 7: `where`

Stage 8: `where`

Stage 9: `mv-expand`

Stage 10: `extend`

Stage 11: `distinct`

Stage 12: `summarize`

Stage 13: `extend`

Stage 14: `where`

Stage 15: `extend` (3 consecutive steps)

Indicators

Output fields

Keyboard shortcuts

Search operators

Detect Potential Kerberoast Activities

MITRE ATT&CK coverage

Rule body kusto

Stages and Predicates

Parameters

Stage 1: source

Stage 2: where

Stage 3: where

Stage 4: extend

Stage 5: extend

Stage 6: project-away

Stage 7: where

Stage 8: where

Stage 9: mv-expand

Stage 10: extend

Stage 11: distinct

Stage 12: summarize

Stage 13: extend

Stage 14: where

Stage 15: extend (3 consecutive steps)

Indicators

Output fields

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `extend`

Stage 5: `extend`

Stage 6: `project-away`

Stage 7: `where`

Stage 8: `where`

Stage 9: `mv-expand`

Stage 10: `extend`

Stage 11: `distinct`

Stage 12: `summarize`

Stage 13: `extend`

Stage 14: `where`

Stage 15: `extend` (3 consecutive steps)