Level-500-Referenz für Architektur, Connectoren, Analytics, Hunting, SOAR, Multi-Tenant-Betrieb und Kostensteuerung in Microsoft Sentinel.Level-500 reference for architecture, connectors, analytics, hunting, SOAR, multi-tenant operations, and cost control in Microsoft Sentinel.
SIEM + SOARSIEM + SOAR
Sentinel verbindet Log Analytics, KQL, UEBA, Playbooks und Incident-Management in einer Cloud-nativen SOC-Plattform.Sentinel combines Log Analytics, KQL, UEBA, playbooks, and incident management in a cloud-native SOC platform.
100+ Connectoren100+ Connectors
Der produktive Mehrwert entsteht durch breite Telemetrie: Microsoft 365, Entra ID, Defender, Azure, Syslog, CEF, AWS, GCP und REST-basierte Quellen.Operational value comes from broad telemetry: Microsoft 365, Entra ID, Defender, Azure, Syslog, CEF, AWS, GCP, and REST-based sources.
KQL & HuntingKQL & Hunting
Scheduled Rules, Near-Real-Time Detection und Proactive Hunting greifen auf dieselben Tabellen, Parser und Content-Hub-Lösungen zu.Scheduled rules, near-real-time detection, and proactive hunting rely on the same tables, parsers, and Content Hub solutions.
SkalierungScale
Commitment Tiers, Basic/Auxiliary Logs, Datenaufbewahrung, ADX-Offload und Data Collection Rules bestimmen Architektur und Kostenprofil.Commitment tiers, basic/auxiliary logs, retention, ADX offload, and data collection rules shape architecture and cost profile.
💡 Portal-Strategie💡 Portal strategy
Microsoft migriert Microsoft Sentinel bis 2027 vollständig in das Defender-Portal. Plane Inhalte, RBAC, Automationsregeln und Analysten-Workflows bereits heute für den Unified-SecOps-Betrieb.Microsoft is moving Microsoft Sentinel fully into the Defender portal by 2027. Plan content, RBAC, automation rules, and analyst workflows today for unified SecOps operations.
Architektur und DatenpfadArchitecture and data path
Microsoft Sentinel baut auf Azure Monitor und einem Log-Analytics-Workspace auf. Eingehende Daten werden über native Connectoren, Azure Monitor Agent, Event Hub, REST-Workflows, CEF/Syslog oder benutzerdefinierte Ingestion APIs normalisiert und landen in Tabellen, die anschließend von Rules, Workbooks, UEBA, TI-Matching und Hunting verwendet werden.Microsoft Sentinel is built on Azure Monitor and a Log Analytics workspace. Incoming data is normalized through native connectors, Azure Monitor Agent, Event Hub, REST workflows, CEF/Syslog, or custom ingestion APIs and lands in tables that are then used by rules, workbooks, UEBA, TI matching, and hunting.
Architekturentscheidungen auf Level 500 betreffen vor allem Workspace-Topologie, DCR-Filterung, Hot-/Cold-Tier, Content-Isolation, Parser-Strategien, Multi-Tenant-Governance und die Frage, welche Daten dauerhaft im Workspace verbleiben und welche nach ADX oder Data Lake ausgelagert werden.Level 500 architecture decisions mainly concern workspace topology, DCR filtering, hot/cold tiering, content isolation, parser strategy, multi-tenant governance, and which data remains in the workspace versus being offloaded to ADX or a data lake.
BausteinComponent
ZweckPurpose
TiefenhinweisDeep-dive note
Log Analytics WorkspaceLog Analytics Workspace
Primärer Speicher- und Query-LayerPrimary storage and query layer
Tabellen wie SigninLogs, SecurityAlert, DeviceProcessEvents oder CommonSecurityLog bilden die Basis für Detection Engineering und Hunting.Tables such as SigninLogs, SecurityAlert, DeviceProcessEvents, or CommonSecurityLog form the basis for detection engineering and hunting.
Sammlung und VorfilterungCollection and pre-filtering
DCRs steuern, welche Windows Events, Syslog Facilities und Custom Logs tatsächlich ingestiert werden und verhindern unnötige Kosten.DCRs control which Windows events, Syslog facilities, and custom logs are ingested, preventing unnecessary cost.
Content HubContent Hub
Bereitstellung von LösungenSolution deployment
Connectoren, Workbooks, Rules, Parser, Playbooks und ARM-Inhalte werden als installierbare Lösungen versioniert ausgeliefert.Connectors, workbooks, rules, parsers, playbooks, and ARM content are delivered as versioned installable solutions.
Analytics EngineAnalytics Engine
Detektion und Incident-ErzeugungDetection and incident generation
Scheduled, NRT, Anomaly, Fusion und Microsoft-Security-Detections greifen auf dieselben Datenmodelle zu, unterscheiden sich aber in Latenz und Betriebsmodell.Scheduled, NRT, anomaly, Fusion, and Microsoft-security detections use the same data models but differ in latency and operating model.
Automation Rules entscheiden, wann Logic Apps ausgelöst werden, Tags gesetzt werden, Incidents geschlossen werden oder Triage-Schritte automatisch laufen.Automation rules determine when Logic Apps run, tags are set, incidents are closed, or triage steps execute automatically.
UEBA / BehaviorAnalyticsUEBA / BehaviorAnalytics
VerhaltensanalyseBehavior analytics
UEBA reichert Identitäten und Entitäten mit InvestigationPriority, Peer Groups und Rare-Behavior-Signalen an.UEBA enriches identities and entities with InvestigationPriority, peer groups, and rare-behavior signals.
Threat IntelligenceThreat Intelligence
IOC-MatchingIOC matching
TI-Indicator-Feeds, TAXII und manuelle Feeds werden gegen Netzwerk-, Endpoint- und Mail-Telemetrie korreliert.TI indicator feeds, TAXII, and manual feeds are correlated against network, endpoint, and email telemetry.
Azure Data ExplorerAzure Data Explorer
Langzeit- oder High-Volume-AnalysenLong-term or high-volume analytics
ADX eignet sich für sehr große Datenmengen, Historisierung jenseits der interaktiven Retention und explorative Data-Science-Workloads.ADX is suitable for very large volumes, history beyond interactive retention, and exploratory data-science workloads.
Ingestion, Hot/Cold-Tier und Multi-WorkspaceIngestion, hot/cold tiers, and multi-workspace
ThemaTopic
Design-EntscheidungDesign decision
Praktischer HinweisOperational note
Hot DataHot data
Interaktive Retention im WorkspaceInteractive retention in the workspace
Für aktive SOC-Daten mit häufigen KQL-Abfragen, Entity Correlation und Incident-Lebenszyklus geeignet.Suitable for active SOC data with frequent KQL queries, entity correlation, and the incident lifecycle.
Archivdaten sind günstiger, aber Rehydration oder Search Jobs erhöhen Latenz und verändern Analysten-Workflows.Archive data is cheaper, but rehydration or search jobs add latency and change analyst workflows.
Für Massenlogs ohne permanenten Analytics-Bedarf nutzen, zum Beispiel verbose Infrastruktur- oder Web-Access-Logs.Use for high-volume logs without a constant analytics need, such as verbose infrastructure or web access logs.
Multi-WorkspaceMulti-workspace
Trennung nach Region, Mandant oder ComplianceSplit by region, tenant, or compliance
Cross-workspace Queries funktionieren, dennoch steigen Governance-Aufwand, Watchlist-Verteilung und Content-Pflege.Cross-workspace queries work, yet governance effort, watchlist distribution, and content maintenance increase.
Dedicated ClusterDedicated cluster
Hochvolumen-WorkspacesHigh-volume workspaces
Bei großen Umgebungen kann ein dedizierter Cluster Performance, Isolation und Kostensteuerung verbessern.In large environments, a dedicated cluster can improve performance, isolation, and cost control.
ADX OffloadADX offload
Historie, Telemetrie-Lake, Advanced AnalyticsHistory, telemetry lake, advanced analytics
Nutze ADX für Long Tail Hunting, ML-Experimente oder Multi-Year-Telemetrie außerhalb interaktiver Sentinel-Nutzung.Use ADX for long-tail hunting, ML experiments, or multi-year telemetry outside interactive Sentinel use.
DCR FilteringDCR filtering
Noise vor dem Ingest reduzierenReduce noise before ingest
Filtere irrelevante Event IDs, Facilities, Hosts oder Felder vor der Abrechnung statt später per KQL.Filter irrelevant event IDs, facilities, hosts, or fields before billing instead of dropping them later with KQL.
Platziere hochkritische Datenquellen möglichst im gleichen Workspace wie die primären Analytics Rules, damit Join-Operationen, UEBA und Entity-Mapping konsistent bleiben.Place highly critical sources in the same workspace as primary analytics rules so join operations, UEBA, and entity mapping stay consistent.
Behandle Parser, Functions und ASIM-Normalisierung als Architekturkomponente; uneinheitliche Feldnamen zerstören Wiederverwendbarkeit von Regeln.Treat parsers, functions, and ASIM normalization as architecture components; inconsistent field names destroy rule reuse.
Plane Multi-Region-Datenhaltung gemeinsam mit Compliance, da Data Residency, Sovereign Clouds und MSSP-Modelle unterschiedliche Workspaces erzwingen können.Plan multi-region data placement with compliance because data residency, sovereign clouds, and MSSP models can require separate workspaces.
Dokumentiere, welche Daten für Live-Erkennung nötig sind und welche nur für Forensik, Reporting oder regulatorische Langzeitaufbewahrung gesammelt werden.Document which data is needed for live detection and which is collected only for forensics, reporting, or regulatory retention.
Connector-Katalog nach TypConnector catalog by type
Die folgende Referenz deckt mehr als 100 gängige Sentinel-Connectoren und Connector-Typen ab. In der Praxis werden viele Lösungen heute über den Content Hub installiert und kombinieren Connector, Parser, Workbook und Rules in einem Paket.The following reference covers more than 100 common Sentinel connectors and connector types. In practice, many solutions are now installed through Content Hub and package connectors, parsers, workbooks, and rules together.
Microsoft 365, Entra ID und DefenderMicrosoft 365, Entra ID, and Defender
Authentifizierung, IPs, CA, MFA und Risiko-Kontext für Identity Detections.Authentication, IPs, CA, MFA, and risk context for identity detections.
Entra ID Audit LogsEntra ID Audit Logs
AuditLogsAuditLogs
Administrative Änderungen, App-Consent, Rollenänderungen und Provisioning-Aktionen.Administrative changes, app consent, role changes, and provisioning actions.
Entra ID Provisioning LogsEntra ID Provisioning Logs
AADProvisioningLogsAADProvisioningLogs
SCIM- und Synchronisationsfehler, die oft Indikatoren für Missbrauch oder Betriebsfehler sind.SCIM and sync failures that often signal misuse or operational issues.
Entra ID Identity ProtectionEntra ID Identity Protection
Einheitliche Alerts aus Endpoint, Identity, Cloud Apps und Office 365.Unified alerts from endpoint, identity, cloud apps, and Office 365.
Defender for EndpointDefender for Endpoint
Device* tablesDevice* tables
Prozess-, Netzwerk-, Registry- und File-Telemetrie für Endpoint Hunting.Process, network, registry, and file telemetry for endpoint hunting.
Defender for Office 365Defender for Office 365
Email* tables / AlertsEmail* tables / Alerts
Mailflow, URL-Klicks, Attachments und AIR-Signale aus E-Mail-Kampagnen.Mail flow, URL clicks, attachments, and AIR signals from email campaigns.
Defender for IdentityDefender for Identity
Identity* / AlertsIdentity* / Alerts
On-Prem-AD-Angriffe wie Kerberoasting, DCSync, DCShadow und lateral movement.On-prem AD attacks such as Kerberoasting, DCSync, DCShadow, and lateral movement.
Defender for Cloud AppsDefender for Cloud Apps
CloudAppEventsCloudAppEvents
SaaS-Aktivitäten, Session Control und OAuth-App-Risiken.SaaS activity, session control, and OAuth app risk.
Microsoft Defender for CloudMicrosoft Defender for Cloud
Cloud workload alerts, posture findings und Secure Score Signale.Cloud workload alerts, posture findings, and Secure Score signals.
Office 365Office 365
OfficeActivityOfficeActivity
SharePoint-, OneDrive-, Teams- und Exchange-Aktivitäten für Insider- und Exfil-Detections.SharePoint, OneDrive, Teams, and Exchange activity for insider and exfil detections.
Compliance-Audit, DLP und sensitivitätsbezogene Aktionen in M365.Compliance audit, DLP, and sensitivity-related actions in M365.
Microsoft Graph SecurityMicrosoft Graph Security
SecurityAlertSecurityAlert
Aggregator für Sicherheitsanbieter, wenn native Connectoren nicht möglich oder nicht gewünscht sind.Aggregator for security vendors when native connectors are not possible or desired.
Microsoft Defender Vulnerability ManagementMicrosoft Defender Vulnerability Management
DeviceTvm*DeviceTvm*
Exposure- und Schwachstellenkontext zur Priorisierung von Incidents.Exposure and vulnerability context for incident prioritization.
Internet-exponierte Assets, Brand Exposure und Shadow-IT-Kontext.Internet-exposed assets, brand exposure, and shadow-IT context.
Microsoft Defender for IoTMicrosoft Defender for IoT
SecurityAlert / IoT logsSecurityAlert / IoT logs
OT- und ICS-Telemetrie, Anomalien und Geräteinventare.OT and ICS telemetry, anomalies, and device inventories.
Microsoft Security Copilot artifactsMicrosoft Security Copilot artifacts
Custom / incidentsCustom / incidents
Optionaler Kontext aus AI-gestützter Triage und empfohlenen Investigation-Schritten.Optional context from AI-assisted triage and recommended investigation steps.
Azure Control Plane und PlattformAzure control plane and platform
ConnectorConnector
Typische Tabelle / ZielTypical table / target
Primärer NutzenPrimary value
Azure ActivityAzure Activity
AzureActivityAzureActivity
Subscription- und Management-Plane-Events für Change Tracking und Privileged Operations.Subscription and management-plane events for change tracking and privileged operations.
NetScaler-Zugriffe, WAF-Ereignisse und ICA-kontextbezogene Daten.NetScaler access, WAF events, and ICA-related telemetry.
Zscaler Internet AccessZscaler Internet Access
CommonSecurityLog / APICommonSecurityLog / API
Proxy-, DLP- und Web-Policy-Kontext für Web Filtering und Exfil.Proxy, DLP, and web-policy context for web filtering and exfil.
NetskopeNetskope
CommonSecurityLog / APICommonSecurityLog / API
SASE-, CASB- und DLP-Events mit Benutzer- und SaaS-Kontext.SASE, CASB, and DLP events with user and SaaS context.
Blue Coat ProxySGBlue Coat ProxySG
CommonSecurityLogCommonSecurityLog
URL, Category, User und Action für Proxy- und Webzugriffe.URL, category, user, and action for proxy and web access.
Imperva WAFImperva WAF
CommonSecurityLogCommonSecurityLog
App-Layer-Schutzsignale und Web-Request-Anomalien.App-layer protection signals and web request anomalies.
Barracuda WAFBarracuda WAF
CommonSecurityLogCommonSecurityLog
WAF-Regeltreffer, Threat Signatures und virtuelle Patches.WAF rule hits, threat signatures, and virtual patches.
AkamaiAkamai
Syslog / APISyslog / API
Edge-, WAF- und Bot-Manager-Signale aus Internet Edge Services.Edge, WAF, and bot manager signals from internet edge services.
SaaS, IAM und CollaborationSaaS, IAM, and collaboration
ConnectorConnector
Typische Tabelle / ZielTypical table / target
Primärer NutzenPrimary value
Okta System LogOkta System Log
Custom / APICustom / API
Okta-Authentifizierungen, MFA, Device Trust und Admin-Änderungen.Okta authentications, MFA, device trust, and admin changes.
Duo SecurityDuo Security
Custom / APICustom / API
MFA-Events, Device Health und Policy-Rejections.MFA events, device health, and policy rejections.
Ping IdentityPing Identity
Custom / APICustom / API
SSO- und Federation-Ereignisse inklusive Token- und Policy-Änderungen.SSO and federation events including token and policy changes.
Google WorkspaceGoogle Workspace
Custom / APICustom / API
Admin Audit, Login-Aktivität und SaaS-Kollaborationsereignisse.Admin audit, login activity, and SaaS collaboration events.
Slack Audit LogsSlack Audit Logs
Custom / APICustom / API
Workspace-Administration, App-Installationen und Datenzugriffe.Workspace administration, app installations, and data access.
Zoom Audit LogsZoom Audit Logs
Custom / APICustom / API
Meeting-, Recording- und Admin-Änderungen für Collaboration-Sicherheit.Meeting, recording, and admin changes for collaboration security.
Dropbox BusinessDropbox Business
Custom / APICustom / API
Sharing, external collaboration und Massendownloads.Sharing, external collaboration, and mass downloads.
Box EventsBox Events
Custom / APICustom / API
Dateiaktivitäten, Freigaben und App-Aktionen in Cloud Content.File activity, sharing, and application actions in cloud content.
GitHub Enterprise AuditGitHub Enterprise Audit
Custom / APICustom / API
Repo-Admin, PAT-Missbrauch, OAuth-Apps und Actions-bezogene Changes.Repo admin, PAT misuse, OAuth apps, and Actions-related changes.
Atlassian Cloud AuditAtlassian Cloud Audit
Custom / APICustom / API
Jira- und Confluence-Admin-Aktionen, API Tokens und Gruppenänderungen.Jira and Confluence admin actions, API tokens, and group changes.
ServiceNowServiceNow
Custom / APICustom / API
ITSM- und CMDB-Kontext für Incident Enrichment und Change Governance.ITSM and CMDB context for incident enrichment and change governance.
SalesforceSalesforce
Custom / APICustom / API
Admin-, Login- und Datenexport-Signale aus CRM-Workloads.Admin, login, and data export signals from CRM workloads.
Cloudflare Zero TrustCloudflare Zero Trust
Custom / APICustom / API
Access, Gateway, WARP und DNS-Signale aus Zero-Trust-Zugängen.Access, gateway, WARP, and DNS signals from zero trust access.
MimecastMimecast
Custom / APICustom / API
Mail-Security-, Archive- und User-Awareness-Telemetrie.Mail security, archive, and user-awareness telemetry.
Proofpoint TAPProofpoint TAP
Custom / APICustom / API
URL Defense, Attachment Defense und Kampagnen-Indikatoren.URL defense, attachment defense, and campaign indicators.
Jamf ProJamf Pro
Custom / APICustom / API
macOS-Geräteinventar, Compliance und Script-Execution-Kontext.macOS inventory, compliance, and script execution context.
CrowdStrike FalconCrowdStrike Falcon
Custom / APICustom / API
EDR Alerts und Device Context zur Multi-EDR-Korrelation.EDR alerts and device context for multi-EDR correlation.
AWS und Multi-CloudAWS and multi-cloud
ConnectorConnector
Typische Tabelle / ZielTypical table / target
Primärer NutzenPrimary value
AWS CloudTrailAWS CloudTrail
AWSCloudTrailAWSCloudTrail
Management- und Data-Plane-Aktivitäten für IAM-, S3- und Control-Plane-Überwachung.Management and data-plane activity for IAM, S3, and control-plane monitoring.
AWS GuardDutyAWS GuardDuty
AWSGuardDutyAWSGuardDuty
Managed detections aus AWS für Findings, EC2, IAM und S3.Managed detections from AWS for findings, EC2, IAM, and S3.
AWS Security HubAWS Security Hub
AWS* findingsAWS* findings
Aggregierte Findings aus AWS Security Services zur Zentralisierung.Aggregated findings from AWS security services for centralization.
AWS VPC Flow LogsAWS VPC Flow Logs
AWSVPCFlowAWSVPCFlow
Netzwerkflüsse für Ost-West- und Exfil-Diagnosen.Network flows for east-west and exfil diagnostics.
AWS WAFAWS WAF
AWSWAFAWSWAF
HTTP Layer Detections, Bot Traffic und Block-Aktionen.HTTP layer detections, bot traffic, and block actions.
AWS Route 53 ResolverAWS Route 53 Resolver
AWSRoute53ResolverAWSRoute53Resolver
DNS-Abfragen und Resolver-Patterns in AWS.DNS queries and resolver patterns in AWS.
AWS CloudWatchAWS CloudWatch
Custom / eventsCustom / events
Service-spezifische Logs, Alarme und Events aus CloudWatch.Service-specific logs, alarms, and events from CloudWatch.
AWS ConfigAWS Config
AWSConfigAWSConfig
Configuration Drift und Compliance Changes in AWS.Configuration drift and compliance changes in AWS.
AWS EKS AuditAWS EKS Audit
AWSEKSAWSEKS
Kubernetes Audit Trail für Cluster und Pod-Aktionen.Kubernetes audit trail for cluster and pod actions.
AWS S3 AccessAWS S3 Access
AWSS3AccessAWSS3Access
Object-Level Access, ungewöhnliche Reads und Public Exposure.Object-level access, unusual reads, and public exposure.
AWS InspectorAWS Inspector
AWSInspectorAWSInspector
Schwachstellen- und Exposure-Findings aus AWS-Workloads.Vulnerability and exposure findings from AWS workloads.
GCP Cloud Audit LogsGCP Cloud Audit Logs
GCPCAuditGCPCAudit
Admin-, Data-Access- und System-Events in GCP.Admin, data access, and system events in GCP.
GCP VPC Flow LogsGCP VPC Flow Logs
GCPVPCFlowGCPVPCFlow
Netzwerkströme für Cloud-Network-Hunting in GCP.Network flows for cloud network hunting in GCP.
GCP Security Command CenterGCP Security Command Center
GCPSCCGCPSCC
Findings aus Container-, IAM- und Storage-Sicherheitskontrollen.Findings from container, IAM, and storage security controls.
GCP Cloud IDSGCP Cloud IDS
GCPIDSGCPIDS
Intrusion-Detections und Signaturen für GCP-Traffic.Intrusion detections and signatures for GCP traffic.
GKE Audit LogsGKE Audit Logs
GKEAuditGKEAudit
Kubernetes Audit auf Google Kubernetes Engine.Kubernetes audit on Google Kubernetes Engine.
Google Workspace Alert CenterGoogle Workspace Alert Center
WorkspaceAlertsWorkspaceAlerts
Sicherheitsrelevante Google-SaaS-Alerts für Cross-Platform Correlation.Security-relevant Google SaaS alerts for cross-platform correlation.
Empfängt Ereignisse direkt in Logic Apps und schreibt sie anschließend in Sentinel.Receives events directly in Logic Apps and then writes them to Sentinel.
Azure Function ConnectorsAzure Function Connectors
Custom tablesCustom tables
Für periodische Pull-Integrationen, Token-Rotation und Transformation.For periodic pull integrations, token rotation, and transformation.
Microsoft Sentinel RepositoriesMicrosoft Sentinel Repositories
Deployment contentDeployment content
Versioniert ARM/Bicep/Terraform- oder GitOps-Inhalte für Regeln, Parser und Playbooks.Versions ARM/Bicep/Terraform or GitOps content for rules, parsers, and playbooks.
Watchlists CSV UploadWatchlists CSV Upload
WatchlistWatchlist
Referenzdaten wie VIP-User, Assets, TLP-Zuordnung oder Geo-Ausnahmen.Reference data such as VIP users, assets, TLP mapping, or geo exceptions.
Normierte IOC-Pipelines aus TIPs, CERTs oder ISACs.Standardized IOC pipelines from TIPs, CERTs, or ISACs.
Azure Data Explorer FederationAzure Data Explorer Federation
External / ADXExternal / ADX
Historische oder massive Datenmengen per Kusto-Federation einbinden.Bring in historical or massive datasets through Kusto federation.
Custom JSON via AMACustom JSON via AMA
Custom tablesCustom tables
Lokale Agents lesen strukturierte JSON-Files mit DCR-Transformationen ein.Local agents ingest structured JSON files with DCR transformations.
Custom Text Logs via AMACustom Text Logs via AMA
Custom tablesCustom tables
Geeignet für Appliances oder Apps, die nur Flat Files erzeugen.Suitable for appliances or applications that only emit flat files.
Syslog over ArcSyslog over Arc
SyslogSyslog
Hybrid- und Edge-Hosts ohne klassische Azure-VM-Anbindung konsolidieren.Consolidate hybrid and edge hosts without classic Azure VM attachment.
OT / ICS Vendor FeedsOT / ICS Vendor Feeds
Custom / IoTCustom / IoT
Speziallösungen aus Fertigung oder Energie über REST, Syslog oder Defender for IoT.Specialized manufacturing or energy solutions via REST, Syslog, or Defender for IoT.
Analytics Rules und KQL-MusterAnalytics rules and KQL patterns
RegeltypRule type
Wann einsetzenWhen to use
KernmerkmalCore characteristic
ScheduledScheduled
Für wiederkehrende Korrelationen mit definierter AbfragefrequenzFor recurring correlations with a defined query frequency
Volle KQL-Flexibilität, Suppression, Entity Mapping und Tactics-Mapping.Full KQL flexibility, suppression, entity mapping, and tactics mapping.
Near-real-time (NRT)Near-real-time (NRT)
Für extrem kurze Erkennungszeit bei klaren ConditionsFor extremely short detection latency on clear conditions
Sekundenschnelle Ausführung mit engeren KQL-Constraints und Fokus auf Speed.Sub-minute execution with tighter KQL constraints and a focus on speed.
Microsoft SecurityMicrosoft Security
Wenn Microsoft-Produkte bereits hochwertige Alerts erzeugenWhen Microsoft products already generate high-quality alerts
Sentinel übernimmt oder ergänzt Alerts aus Defender, Entra und weiteren Microsoft-Quellen.Sentinel consumes or enriches alerts from Defender, Entra, and other Microsoft sources.
FusionFusion
Für Multi-Stage-Korrelation ohne eigene ModellierungFor multi-stage correlation without custom modeling
ML-gestützte Verknüpfung mehrerer Low-Signal-Events zu einem hochwertigen Incident.ML-driven linking of multiple low-signal events into a higher-quality incident.
AnomalyAnomaly
Für Verhalten, Volumen und Rare-Pattern-DektionenFor behavior, volume, and rare-pattern detections
Baselines und Lernmodelle identifizieren ungewöhnliche Aktivität jenseits statischer Schwellwerte.Baselines and learning models identify unusual activity beyond static thresholds.
Erfolgreiche Sign-ins aus mehreren Ländern am selben TagSuccessful sign-ins from multiple countries on the same day
KQLKQL
SigninLogs
| where ResultType == 0
| summarize Countries = make_set(LocationDetails.countryOrRegion), IPs = dcount(IPAddress) by UserPrincipalName, bin(TimeGenerated, 1d)
| where array_length(Countries) > 1 and IPs > 1
| project TimeGenerated, UserPrincipalName, Countries, IPs
MFA-Fatigue durch wiederholte Prompt-AblehnungenMFA fatigue through repeated prompt denials
KQLKQL
SigninLogs
| where ResultType != 0
| where Status.failureReason has_any ("MFA denied", "user declined", "fraud")
| summarize Denials = count(), Apps = make_set(AppDisplayName) by UserPrincipalName, IPAddress, bin(TimeGenerated, 15m)
| where Denials >= 5
Rollenänderungen in privilegierten Entra-GruppenRole changes in privileged Entra groups
KQLKQL
AuditLogs
| where OperationName has_any ("Add member to role", "Add eligible member to role")
| extend InitiatedByUser = tostring(InitiatedBy.user.userPrincipalName)
| project TimeGenerated, OperationName, InitiatedByUser, TargetResources
AuditLogs
| where OperationName has_any ("Consent to application", "Add delegated permission grant")
| project TimeGenerated, OperationName, InitiatedBy, TargetResources, AdditionalDetails
Encoded PowerShell auf EndpunktenEncoded PowerShell on endpoints
KQLKQL
DeviceProcessEvents
| where FileName in~ ("powershell.exe", "pwsh.exe")
| where ProcessCommandLine has_any ("-enc", "-encodedcommand", "FromBase64String")
| project Timestamp, DeviceName, AccountName, ProcessCommandLine
Seltene ausgehende DomainsRare outbound domains
KQLKQL
DeviceNetworkEvents
| where isnotempty(RemoteUrl)
| summarize Hits = count(), Devices = dcount(DeviceName) by RemoteUrl
| where Hits < 5 and Devices < 3
| order by Hits asc
Mailbox-Forwarding und Inbox-RegelnMailbox forwarding and inbox rules
KQLKQL
OfficeActivity
| where OfficeWorkload == "Exchange"
| where Operation in ("New-InboxRule", "Set-InboxRule", "Set-Mailbox")
| where Parameters has_any ("ForwardTo", "RedirectTo", "DeliverToMailboxAndForward")
| project TimeGenerated, UserId, Operation, Parameters
Massendownloads in SharePoint/OneDriveMass downloads in SharePoint/OneDrive
KQLKQL
OfficeActivity
| where OfficeWorkload in ("SharePoint", "OneDrive")
| where Operation in ("FileDownloaded", "FileSyncDownloadedFull")
| summarize Downloads = count(), Files = dcount(SourceFileName) by UserId, bin(TimeGenerated, 30m)
| where Downloads > 250 or Files > 100
GuardDuty High Severity FindingsGuardDuty high severity findings
KQLKQL
AWSGuardDuty
| where Severity >= 7
| summarize Findings = count() by Title, AccountId, Region, bin(TimeGenerated, 1h)
| order by Findings desc
Firewall-Deny-Spikes aus CEFFirewall deny spikes from CEF
KQLKQL
CommonSecurityLog
| where DeviceAction =~ "Deny"
| summarize Denies = count() by DeviceVendor, SourceIP, DestinationPort, bin(TimeGenerated, 10m)
| where Denies > 100
let ti = ThreatIntelligenceIndicator
| where Active == true and ExpirationDateTime > now()
| project IndicatorId, NetworkIP, DomainName, Url;
DeviceNetworkEvents
| join kind=innerunique ti on $left.RemoteIP == $right.NetworkIP
| project Timestamp, DeviceName, RemoteIP, IndicatorId
UEBA High Investigation PriorityUEBA high investigation priority
KQLKQL
BehaviorAnalytics
| where InvestigationPriority >= 5
| summarize Entities = make_set(Entities), Signals = count() by UserName, ActivityType, bin(TimeGenerated, 1d)
| order by Signals desc
NRT-Kandidat für Password SprayNRT candidate for password spray
KQLKQL
SigninLogs
| where ResultType != 0
| summarize Failed = count(), Users = dcount(UserPrincipalName) by IPAddress, bin(TimeGenerated, 5m)
| where Failed > 25 and Users > 10
Fusion-Nachverfolgung über SecurityAlertFusion follow-up through SecurityAlert
KQLKQL
SecurityAlert
| where ProductName =~ "Azure Sentinel"
| where AlertName has "Fusion"
| project TimeGenerated, AlertName, CompromisedEntity, ExtendedProperties
Incident Aging und SOC BacklogIncident aging and SOC backlog
KQLKQL
SecurityIncident
| extend AgeHours = datetime_diff('hour', now(), CreatedTime)
| summarize OpenIncidents = count(), AvgAge = avg(AgeHours) by Severity, Status
Neu auftretende Prozesse pro HostNew processes per host
KQLKQL
DeviceProcessEvents
| summarize FirstSeen=min(Timestamp), LastSeen=max(Timestamp) by DeviceName, FileName, SHA1
| where FirstSeen > ago(24h)
| order by FirstSeen desc
MITRE ATT&CK, Incidents und Investigation GraphMITRE ATT&CK, incidents, and investigation graph
BereichArea
Sentinel-MechanikSentinel mechanism
SOC-NutzenSOC value
MITRE MappingMITRE mapping
Rules mappen Tactics und Techniques direkt im Detection-ObjektRules map tactics and techniques directly on the detection object
Analysten sehen sofort Kill-Chain-Kontext und können Coverage-Lücken pro Tactic identifizieren.Analysts immediately see kill-chain context and can identify coverage gaps by tactic.
IncidentsIncidents
Alerts werden per Incident Settings gruppiertAlerts are grouped through incident settings
Richtiges Grouping reduziert Alarmflut und vereint Mail-, Identity- und Endpoint-Signale in einer Story.Proper grouping reduces alert storms and unifies email, identity, and endpoint signals into one story.
Investigation GraphInvestigation graph
Entitäten wie User, Host, IP, Mailbox und URL werden graphisch verbundenEntities such as users, hosts, IPs, mailboxes, and URLs are connected visually
Hilft besonders bei lateraler Bewegung und bei Multi-Signal-Incidents aus Defender XDR plus Drittquellen.Especially helpful for lateral movement and multi-signal incidents from Defender XDR plus third-party sources.
Entity MappingEntity mapping
KQL-Ausgaben werden auf standardisierte Entitätstypen gemapptKQL outputs are mapped to standardized entity types
Ohne sauberes Entity Mapping verlieren Incidents Graph, UEBA und Investigation Features deutlich an Qualität.Without clean entity mapping, incidents lose significant graph, UEBA, and investigation quality.
⚠️ Incident-Tuning⚠️ Incident tuning
Zu aggressive Incident-Gruppierung verschmilzt unterschiedliche Angriffsketten; zu konservative Gruppierung erzeugt Analysten-Rauschen. Tune Rules, Reopen-Logik und Grouping gemeinsam.Overly aggressive incident grouping merges unrelated attack chains; overly conservative grouping creates analyst noise. Tune rules, reopen logic, and grouping together.
SOAR: Automation Rules und PlaybooksSOAR: automation rules and playbooks
BausteinBuilding block
BeispielExample
Wichtig für BetriebOperational importance
Automation RuleAutomation rule
Tagge High-Fidelity-Identity-Incidents automatisch mit 'Tier1-AutoTriage'Automatically tag high-fidelity identity incidents with 'Tier1-AutoTriage'
Regeln steuern Playbook-Auslösung, Ownership, Severity-Updates und automatische Schließung.Rules control playbook triggers, ownership, severity changes, and automatic closure.
Playbook via Logic AppsPlaybook via Logic Apps
Entra User suspendieren, Teams-Nachricht senden, Ticket erstellenSuspend an Entra user, send a Teams message, create a ticket
Playbooks sind am wertvollsten, wenn sie Idempotenz, Fehlerpfade und Rückmeldung an den Incident unterstützen.Playbooks are most valuable when they support idempotency, failure paths, and write-back to the incident.
TemplateTemplate
Prebuilt Playbooks aus Content HubPrebuilt playbooks from Content Hub
Templates beschleunigen den Start, müssen aber Security Reviews, Secrets Management und Naming Standards erfüllen.Templates accelerate adoption, but must pass security review, secret management, and naming standards.
Managed IdentityManaged identity
Playbook greift sicher auf Graph, Azure oder ServiceNow zuPlaybook securely accesses Graph, Azure, or ServiceNow
Vermeidet statische Secrets und vereinfacht Rotation, RBAC und Auditing.Avoids static secrets and simplifies rotation, RBAC, and auditing.
PowerShell mit Az.SecurityInsightsPowerShell with Az.SecurityInsights
Executive Dashboards, Detection Coverage, Identity Risk, Connector Health und MSSP-Sicht auf Kundenmandanten.Executive dashboards, detection coverage, identity risk, connector health, and MSSP views across customer tenants.
UEBAUEBA
BehaviorAnalytics, Identity, Device, Cloud SignaleBehaviorAnalytics, identity, device, and cloud signals
IOC-Enrichment, outbound C2 detection, email URL hits und Firewall/IP-Korrelation.IOC enrichment, outbound C2 detection, email URL hits, and firewall/IP correlation.
BookmarksBookmarks
Hunting-ErgebnisseHunting results
Persistiert Untersuchungsartefakte, die später in Incidents, Playbooks oder weiteren Hunts auftauchen.Persists investigative artifacts that can later show up in incidents, playbooks, or additional hunts.
Hunting, Bookmarks, Livestream und NotebooksHunting, bookmarks, livestream, and notebooks
Advanced Hunting in Sentinel ist nicht nur KQL auf Tabellen. Effektive Hunting-Programme standardisieren Bookmark-Konventionen, nutzen Livestream für aktive Incidents, korrelieren Defender-XDR-Tabellen mit Netzwerkdaten und dokumentieren Hypothesen in wiederverwendbaren Hunt-Queries.Advanced hunting in Sentinel is not just KQL on tables. Effective hunting programs standardize bookmark conventions, use livestream during active incidents, correlate Defender XDR tables with network data, and document hypotheses in reusable hunt queries.
WerkzeugTool
StärkeStrength
Wann sinnvollWhen useful
Hunting QueriesHunting queries
Schnelle HypothesentestsFast hypothesis testing
Für Analysten, die in Minuten neue Fragen an Telemetrie stellen müssen.For analysts who need to ask new questions of telemetry within minutes.
LivestreamLivestream
Nahezu Echtzeit-Sicht auf frisch eingehende DatenNear-real-time view of fresh incoming data
Während aktiver Angriffe, um laufende Prozess- oder Sign-in-Ereignisse zu beobachten.During active attacks to watch live process or sign-in activity.
BookmarksBookmarks
Persistente MarkierungenPersistent markers
Zum Übergang von Threat Hunting in Incident Response und für Peer Review zwischen Schichten.For transitioning from threat hunting into incident response and peer review between shifts.
MSTICPyMSTICPy
Python-Analytik auf Kusto, TI und NotebooksPython analytics across Kusto, TI, and notebooks
Wenn Data Science, enrichment pipelines oder Visualisierung über reines KQL hinausgehen.When data science, enrichment pipelines, or visualization go beyond pure KQL.
Jupyter / NotebooksJupyter / notebooks
Mehrstufige Analysen und Case NarrativesMulti-step analysis and case narratives
Für umfangreiche Investigations, Malware Clustering oder wiederholbare DFIR-Workflows.For extensive investigations, malware clustering, or repeatable DFIR workflows.
KQLKQL
let suspiciousIps = materialize(
SigninLogs
| where TimeGenerated > ago(1d)
| where ResultType == 0
| summarize Users = dcount(UserPrincipalName) by IPAddress
| where Users > 20
);
DeviceNetworkEvents
| where Timestamp > ago(1d)
| join kind=inner suspiciousIps on $left.RemoteIP == $right.IPAddress
| summarize Connections = count() by DeviceName, RemoteIP, RemoteUrl
PythonPython
from msticpy.data import QueryProvider
qry = QueryProvider("MSSentinel")
qry.connect(workspace="law-soc-prod")
result = qry.exec_query("SigninLogs | take 10")
result.head()
Content Hub, Watchlists und RepositoriesContent Hub, watchlists, and repositories
CapabilityCapability
BeispielExample
HinweisNote
Content Hub SolutionsContent Hub solutions
Microsoft Defender for Endpoint, Palo Alto, OktaMicrosoft Defender for Endpoint, Palo Alto, Okta
Behandle Solutions wie Code: versionieren, testen, dokumentieren und Freigabeprozesse definieren.Treat solutions like code: version, test, document, and define release processes.
WatchlistsWatchlists
VIPs, High Value Assets, Sanctioned IP RangesVIPs, high value assets, sanctioned IP ranges
ARM/Bicep/Terraform/KQL in GitARM/Bicep/Terraform/KQL in Git
CI/CD für detections ermöglicht Peer Review, Branch Policies, Pull Requests und reproduzierbare Deployments.CI/CD for detections enables peer review, branch policies, pull requests, and reproducible deployments.
Parser & FunctionsParsers and functions
ASIM-Normalisierung für NetworkSession, Authentication, DNSASIM normalization for NetworkSession, Authentication, DNS
Ohne zentrale Parser wird jede neue Rule teurer und schwieriger wartbar.Without central parsers, every new rule becomes more expensive and harder to maintain.
Kostenmanagement und DatensteuerungCost management and data control
HebelLever
WirkungEffect
PraxisPractice
Commitment TiersCommitment tiers
Preis sinkt bei planbarer TagesmengePrice decreases when daily volume is predictable
Sinnvoll für stabile SOC-Workloads; monatlich prüfen, ob Peak- und Durchschnittsvolumen den Tier rechtfertigen.Useful for stable SOC workloads; review monthly whether peak and average volume justify the tier.
Freie DatenquellenFree data sources
Einige Microsoft-Signale verursachen reduzierte oder keine Ingest-KostenSome Microsoft signals carry reduced or no ingest cost
Defender- und Aktivitätsdatenmodelle regelmäßig gegen aktuelle Preislisten und Produktdokumentation verifizieren.Regularly verify Defender and activity data models against current pricing and product documentation.
Data Collection RulesData collection rules
Noise vor der Abrechnung entfernenRemove noise before billing
Event IDs, Facilities, Hosts und Parser schon beim Ingest minimieren.Minimize event IDs, facilities, hosts, and parsers at ingest time.
RetentionRetention
Interaktive Datenmenge reduzierenReduce interactive data volume
Aktive 30 bis 90 Tage im Workspace, Langzeitdaten archivieren oder nach ADX verschieben.Keep active 30 to 90 days in the workspace and archive or offload long-term data to ADX.
Sampling / SummariesSampling / summaries
Kostengünstigere Use CasesLower-cost use cases
Nicht jede hochvolumige Quelle muss roh und vollständig ingestiert werden; Summaries genügen oft für Monitoring.Not every high-volume source must be ingested raw and in full; summaries are often enough for monitoring.
Parser ReuseParser reuse
Analysten-Zeit sparenSave analyst time
Konsistente Functions und ASIM sparen Query-Kosten und reduzieren Fehler in allen Teams.Consistent functions and ASIM save query time and reduce errors across teams.
KQLKQL
Usage
| where TimeGenerated > ago(14d)
| summarize GB = sum(Quantity) / 1024 by DataType, Solution, bin(TimeGenerated, 1d)
| order by TimeGenerated desc, GB desc
Multi-Tenant, Lighthouse und MigrationMulti-tenant, Lighthouse, and migration
SzenarioScenario
MusterPattern
HinweisNote
MSSP via Azure LighthouseMSSP via Azure Lighthouse
Delegierter Zugriff auf Kunden-Subscriptions und WorkspacesDelegated access to customer subscriptions and workspaces
Ideal für zentrale Bearbeitung, aber RBAC, Data Residency und Incident Ownership sauber modellieren.Ideal for centralized operations, but model RBAC, data residency, and incident ownership carefully.
Connectoren in Kundenmandanten, SOC-Views im Provider-KontextConnectors in customer tenants, SOC views in the provider context
Achte auf Consent, cross-tenant diagnostics und getrennte Playbook-Identitäten.Watch consent, cross-tenant diagnostics, and separate playbook identities.
Splunk-MigrationSplunk migration
SPL nach KQL, CIM nach ASIM, Forwarder-Use-Cases nach AMA/Event HubSPL to KQL, CIM to ASIM, forwarder use cases to AMA/Event Hub
Beginne mit High-Value Use Cases statt 1:1 Dashboard- oder Index-Replikation.Start with high-value use cases instead of 1:1 dashboard or index replication.
QRadar-MigrationQRadar migration
Offense-Modelle in Incidents, DSM/Log Sources in Connectoren und Parser übertragenTranslate offense models into incidents, DSM/log sources into connectors and parsers
Mapping von Regeln, Referenzsets und Use Cases vorab dokumentieren und priorisieren.Document and prioritize mapping of rules, reference sets, and use cases upfront.
Coexistence-PhaseCoexistence phase
Parallelbetrieb mit abgestimmten Schweregraden und OwnershipParallel run with aligned severities and ownership
Verhindere Doppelalarme durch klares Routing, deduplizierte Ticketpfade und abgestimmte Use-Case-Verantwortung.Prevent duplicate alerts through clear routing, deduplicated ticketing paths, and aligned use-case ownership.