Detection rules › Kusto
Quokka - Malicious Results Detected
'Detects if there are any malicious results in the app events coming from organization devices.'
MITRE ATT&CK coverage
Rule body kusto
id: 97ad71ed-e4c0-4f7a-b1a2-683108bece4f
name: Quokka - Malicious Results Detected
description: |
'Detects if there are any malicious results in the app events coming from organization devices.'
severity: Medium
status : Available
requiredDataConnectors:
- connectorId: QscoutAppEventsCCFDefinition
dataTypes:
- QscoutAppEvents_CL
queryFrequency: 1h
queryPeriod: 1h
triggerOperator: gt
triggerThreshold: 0
tactics:
- InitialAccess
- Execution
- Persistence
- PrivilegeEscalation
- DefenseEvasion
- CredentialAccess
- Discovery
- Collection
- CommandAndControl
- Impact
relevantTechniques:
- T1406
- T1409
- T1414
- T1417
- T1418
- T1422
- T1424
- T1429
- T1430
- T1471
- T1474
- T1481
- T1509
- T1512
- T1513
- T1516
- T1517
- T1532
- T1541
- T1544
- T1582
- T1616
- T1617
- T1623
- T1624
- T1625
- T1627
- T1628
- T1629
- T1630
- T1631
- T1633
- T1634
- T1635
- T1636
- T1638
- T1640
- T1641
- T1642
- T1643
query: |
let timeRange = 1h;
let appEventsWithMaliciousResults = QscoutAppEvents_CL
| extend AccountCustomEntity = tostring(org_id)
| where TimeGenerated >= ago(timeRange)
| where result_type == 'maliciousness'
| where isnotempty(results.entries);
appEventsWithMaliciousResults
| mv-expand entry = results.entries
| project
TimeGenerated,
AccountCustomEntity,
app_id,
mdm_source,
mdm_device_id,
package,
platform,
version,
rule_id = tostring(entry.ruleId),
desription = tostring(entry.description),
threat_level = toint(entry.threatLevel),
threat_types = tostring(entry.threatTypes)
entityMappings:
- entityType: Account
fieldMappings:
- identifier: Name
columnName: AccountCustomEntity
version: 1.0.0
kind: Scheduled
Stages and Predicates
Parameters
let timeRange = 1h;
The stages below define let appEventsWithMaliciousResults (the rule's main pipeline source).
Stage 1: source
QscoutAppEvents_CL
Stage 2: extend
| extend AccountCustomEntity = tostring(org_id)
Stage 3: where
| where TimeGenerated >= ago(timeRange)
Stage 4: where
| where result_type == 'maliciousness'
Stage 5: where
| where isnotempty(results.entries)
The stages below run on appEventsWithMaliciousResults (the outer pipeline).
Stage 6: mv-expand
appEventsWithMaliciousResults
| mv-expand entry = results.entries
Stage 7: project
| project
TimeGenerated,
AccountCustomEntity,
app_id,
mdm_source,
mdm_device_id,
package,
platform,
version,
rule_id = tostring(entry.ruleId),
desription = tostring(entry.description),
threat_level = toint(entry.threatLevel),
threat_types = tostring(entry.threatTypes)
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 |
|---|---|---|
entries | is_not_null | |
result_type | eq |
|
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 |
|---|---|
AccountCustomEntity | project |
TimeGenerated | project |
app_id | project |
desription | project |
mdm_device_id | project |
mdm_source | project |
package | project |
platform | project |
rule_id | project |
threat_level | project |
threat_types | project |
version | project |