Mass Cloud resource deletions Time Series Anomaly

Status: available
Severity: medium
Time window: 14d
Group by: Caller
Source: github.com/Azure/Azure-Sentinel

'This query generates the baseline pattern of cloud resource deletions by an individual and generates an anomaly when any unusual spike is detected. These anomalies from unusual or privileged users could be an indication of a cloud infrastructure takedown by an adversary.'

MITRE ATT&CK coverage

Tactic	Techniques
Impact	`T1485` Data Destruction

Rule body kusto

id: ed43bdb7-eaab-4ea4-be52-6951fcfa7e3b
name: Mass Cloud resource deletions Time Series Anomaly
description: |
  'This query generates the baseline pattern of cloud resource deletions by an individual and generates an anomaly when any unusual spike is detected. These anomalies from unusual or privileged users could be an indication of a cloud infrastructure takedown by an adversary.'
severity: Medium
status: Available 
requiredDataConnectors:
  - connectorId: AzureActivity
    dataTypes:
      - AzureActivity
queryFrequency: 1d
queryPeriod: 14d
triggerOperator: gt
triggerThreshold: 0
tactics:
  - Impact
relevantTechniques:
  - T1485
tags:
  - DEV-0537
query: |
  let starttime = 14d;
  let endtime = 1d;
  let timeframe = 1d;
  let TotalEventsThreshold = 25;
  let TimeSeriesData = AzureActivity 
  | where TimeGenerated between (startofday(ago(starttime))..startofday(now())) 
  | where OperationNameValue endswith "delete" 
  | project TimeGenerated, Caller 
  | make-series Total = count() on TimeGenerated from startofday(ago(starttime)) to startofday(now()) step timeframe by Caller;
  TimeSeriesData 
  | extend (anomalies, score, baseline) = series_decompose_anomalies(Total, 3, -1, 'linefit') 
  | mv-expand Total to typeof(double), TimeGenerated to typeof(datetime), anomalies to typeof(double), score to typeof(double), baseline to typeof(long) 
  | where TimeGenerated >= startofday(ago(endtime)) 
  | where anomalies > 0 
  | project Caller, TimeGenerated, Total, baseline, anomalies, score 
  | where Total > TotalEventsThreshold and baseline > 0 
  | join (AzureActivity 
  | where TimeGenerated > startofday(ago(endtime)) 
  | where OperationNameValue endswith "delete" 
  | summarize count(), make_set(OperationNameValue,100), make_set(_ResourceId,100) by bin(TimeGenerated, timeframe), Caller ) on TimeGenerated, Caller 
  | extend Name = iif(Caller has '@',tostring(split(Caller,'@',0)[0]),"")
  | extend UPNSuffix = iif(Caller has '@',tostring(split(Caller,'@',1)[0]),"")
  | extend AadUserId = iif(Caller !has '@',Caller,"")
entityMappings:
  - entityType: Account
    fieldMappings:
      - identifier: FullName
        columnName: Caller
      - identifier: Name
        columnName: Name
      - identifier: UPNSuffix
        columnName: UPNSuffix
  - entityType: Account
    fieldMappings:
      - identifier: AadUserId
        columnName: AadUserId
version: 2.0.4
kind: Scheduled

Stages and Predicates

Parameters

let starttime = 14d;
let endtime = 1d;
let timeframe = 1d;
let TotalEventsThreshold = 25;

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

Stage 1: `source`

AzureActivity

Stage 2: `where`

| where TimeGenerated between (startofday(ago(starttime))..startofday(now()))

Stage 3: `where`

| where OperationNameValue endswith "delete"

Stage 4: `project`

| project TimeGenerated, Caller

The stages below score time-series anomalies (make-series, series_decompose_anomalies).

Stage 5: `summarize`

| make-series Total = count() on TimeGenerated from startofday(ago(starttime)) to startofday(now()) step timeframe by Caller

Threshold: gt 25

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

Stage 6: `extend`

TimeSeriesData
| extend (anomalies, score, baseline) = series_decompose_anomalies(Total, 3, -1, 'linefit')

Stage 7: `mv-expand`

| mv-expand Total to typeof(double), TimeGenerated to typeof(datetime), anomalies to typeof(double), score to typeof(double), baseline to typeof(long)

Stage 8: `where`

| where TimeGenerated >= startofday(ago(endtime))

Stage 9: `where`

| where anomalies > 0

Stage 10: `project`

| project Caller, TimeGenerated, Total, baseline, anomalies, score

Stage 11: `where`

| where Total > TotalEventsThreshold and baseline > 0

Stage 12: `join`

| join (AzureActivity 
| where TimeGenerated > startofday(ago(endtime)) 
| where OperationNameValue endswith "delete" 
| summarize count(), make_set(OperationNameValue,100), make_set(_ResourceId,100) by bin(TimeGenerated, timeframe), Caller ) on TimeGenerated, Caller

Stage 13: `extend` (3 consecutive steps)

| extend Name = iif(Caller has '@',tostring(split(Caller,'@',0)[0]),"")
| extend UPNSuffix = iif(Caller has '@',tostring(split(Caller,'@',1)[0]),"")
| extend AadUserId = iif(Caller !has '@',Caller,"")

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
`OperationNameValue`	ends_with	`delete`
`Total`	gt	`25` transforms: `cased`
`anomalies`	gt	`0` transforms: `cased`
`baseline`	gt	`0` 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
`Caller`	`project`
`TimeGenerated`	`project`
`Total`	`project`
`anomalies`	`project`
`baseline`	`project`
`score`	`project`
`Name`	`extend`
`UPNSuffix`	`extend`
`AadUserId`	`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)

Mass Cloud resource deletions Time Series Anomaly

MITRE ATT&CK coverage

Rule body kusto

Stages and Predicates

Parameters

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `project`

Stage 5: `summarize`

Stage 6: `extend`

Stage 7: `mv-expand`

Stage 8: `where`

Stage 9: `where`

Stage 10: `project`

Stage 11: `where`

Stage 12: `join`

Stage 13: `extend` (3 consecutive steps)

Indicators

Output fields

Keyboard shortcuts

Search operators

Mass Cloud resource deletions Time Series Anomaly

MITRE ATT&CK coverage

Rule body kusto

Stages and Predicates

Parameters

Stage 1: source

Stage 2: where

Stage 3: where

Stage 4: project

Stage 5: summarize

Stage 6: extend

Stage 7: mv-expand

Stage 8: where

Stage 9: where

Stage 10: project

Stage 11: where

Stage 12: join

Stage 13: extend (3 consecutive steps)

Indicators

Output fields

Stage 1: `source`

Stage 2: `where`

Stage 3: `where`

Stage 4: `project`

Stage 5: `summarize`

Stage 6: `extend`

Stage 7: `mv-expand`

Stage 8: `where`

Stage 9: `where`

Stage 10: `project`

Stage 11: `where`

Stage 12: `join`

Stage 13: `extend` (3 consecutive steps)