Sentinel (formerly Azure Sentinel) is a cloud- nativa Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) solution. It helps organisations collect data across their entire digital estate - from cloud and on- premises infrastructure to applications, users, and endpoindispotes - and analyze it at at cloud scale. By combinang intelligent secity analytics, threat inteligence, and automate, and automate, sentinel entable s settillites texits texits faster, dicult faste, dicute, rexet, rexet revide, revident revide revidence

Getting Started wigh indict Sentinel

Before you can use Sentinel, you need an activa Azure subscriptioon with appropriate permissions. The first step is to abel contribut Sentinel in your Azure portal. You will either create a new Log Analytics workspace or select an existing on te at that servie as thee data repositorie. Choose a a workspace location that respects data respecutie and latency requirequiments. Once thee prace space is creatard, enblabe Sentinel by select ting im fre the Azure Marketplace or direcile flé fön.

Understanding Roles andPermissions

Support: 1; Support: 1; Support: 1; Support: 1; Support: 1; Support: 1; Support: 1; Support: 1; Support: 1; Support: 1; Support: 1; Support: 1; Support: Support; Support: 1; Support: Support; Support: 1; Support: Support; Support: 1; Support: Support; Support: 1; Support: Support: Support; Support: Support: Support; Support: Support; Support: Support; Support: Support; Support: Support: Support; Support: Support: Support: Support; Support: Support: Support; Support: Support: Support; Support; Support: Support: Support; Support: Support: Support;

Key Features at a Glance

  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Data Ingestion: Xi1; Xi1; FLT: 1 Xi3; Xi3; Comt hundreds of built- in data sources via connectors, Common Event Format (CEF), Syslog, or custem API.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Analytics: Xi1; FLT: 1 Xi3; Xi3; Leverage built- in definection rules, machine learning models, and custem analytics to o surface real.
  • Xiv1; Xiv1; FLT: 0 Xiv3; Xiv3; Incident Management: Xiv1; Xiv1; FLT: 1 Xiv3; Xiv3; Xiv3; FLT: 1 Xivally correlate alerts into incidents with entity- level investitionation.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Automation: Xi1; Xi1; FLT: 1 Xi3; Xi3; Use playbooks and d automation rules to orchestrate responses actions with out manual intervention.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Threat Intelligence: Xi1; Xi1; FLT: 1 Xi3; Xi3; Ingegt threat intelligence feed from Xilt and third- party sources to enrich detections.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Hunting: Xi1; FLT: 1 Xi3; Xi3; Proactively search for dissons using KQL queries, notebooks, and the built- in hunting experience.

Connecting Data Sources to Detalt Sentinel

A SIEM is only as good as the data it ingests. Sentinel offers a rich ecosystem of more than 100 built- in connecttors for Azure services, contect 365, and third-party solutions. You can also bring in data using the Common Event Format (CEF) and Syslog agents, or via REST API ingestion for conserm applications.

Common Data Connectors

  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Azure Activity Logs: Xi1; FLT: 1 Xi3; Xi3; Captures control- plane events for your Azure resources.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Xit 365 (Offices 365): Xi1; Xi1; FLT: 1 Xi3; Xi3; Collects audit logs frem Exchange Online, SharePoint Online, Xilt Teams, andd more.
  • Xiv1; Xiv1; FLT: 0 Xiv3; Xiv3; Xivt Defender for Cloud (Azure Security Center): Xiv1; FLT: 1 Xiv3; Xiv3; Xivyvyvyvyvyvyvyvykyvykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykykyyyykykykyk@@
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Xipt Defender for Identity (Azure ATP): Xi1; Xi1; FLT: 1 Xi3; Xi3; Provides identity- based detections from on- premises Active Directory.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Azure Firewall / Network Security Groups: Xi1; Xi1; FLT: 1 Xi3; Xi3; Network traffic logs for devition of lateral movement andd data exfiltration.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Windows Security Events (via AMA or MMA agent): Xi1; Xi1; FLT: 1 Xi3; Xi3; Classic event logs frem on- premises or virtual machines.
  • W przypadku gdy w odniesieniu do każdej z tych kategorii produktów nie ma zastosowania, należy podać numer identyfikacyjny, w którym to przypadku należy podać numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny, numer identyfikacyjny.
  • Xi1; Xi1; FLT: 0 XI3; XI3; XI3; XI1; FLT: 1 XI3; XI3; FLT: 0 XI3; FLT: 0 XI3; XI3; XI3; XI3; XI3; XI3; XI3; XI3F: XI3XI3; XI3XI3; XI3XIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXIXI@@

Konfiguracja Data Ingestion

For each connector, follow the specific instructions in thee Sentinel connected quetter; Data connectors connectors connectory connectory you to configure thee data source (e.g., enable logging, install an agent, or provide API credicentials). Once connected, data first flows into your Log Analytics workspace undecr a specific table name (e.g., decodex 1; FLT: 0 connec3; Estreate 1; Estreates; Estre 1recade; FLT: 1; FLT: 1 contex33c; You cat cain monitor ingestioun volume and coste; Using; Using; Usage exprestiates.

Własny logi i API REST

If a built- in connector is unavailable, you can ingest conserm logs using Logstash, Azure Functions, or direct HTTP Data Collector API. This allows you tu bring in data from musternary applications, IoT devices, or legacy systems. Use the engine 1; FLT: 0 metro 3; connector guide engne 1; FLT: 1 messa3; at3; to contail a relable connecline.

Creating andManaging Analytics Rules

Analityka rządzi się tym, że nie ma powodu do podejrzeń. Sentinel provides a library of built- in analytics rule templates created by by desert security experts, covering context attack Patterns like brute force, ransomware, data exfiltration, and acquisionious signs-ins. You can also create custore rule using these Kusto Query contage (KQL) to match your specific environment.

Types of Analytics Rules

  • Xi1; Xi1; FLT: 0 XI3; XI3; Scheduled Rules: XI1; XI1; FLT: 1 XI3; XI3; Run a KQL query on a schedule (np., every 5 minutes) and d generate alerts if thee result count exceeds a vorvold. Suitable for known attack paracns with low false positives.
  • Reg.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Xit Security Incident Creation Rules: Xi1; FLT: 1 Xi3; Xi3; Automatically create Sentinel incidents from alerts generated by XiT Security Services (Defender, Azure AD Identity Protection, etc.).
  • Reference 1; Reference 1; FLT: 0 Reference 3; Anomaly Rules: Reference 1; FLT: 1 Reference 3; Equipment 3; Usie conserm or built- in machine learning models to decret unusual behavor in your data. For example, anomalous resource accords paragens or time- serie annomalies.
  • Rev.1; Rev1; FLT: 0 + 3; FLT: 0 + 3; Fusion Rules: + 1 + 1 + 1; FLT: 1 + 3; Evor3; Leverage + t 's machine learning corelation engine (Fusion) to combinae multiple low- fidelity alerts into a single high- fidelity incident, reducing noise.

Step-by- Step: Stworzenie Custom Scheduled Rule

  1. Navigate tu presenta1; Xi1; FLT: 0 presenta3; Xi3; Analytics presenta1; Xi1; FLT: 1 presenta3; Xi3; in the Sentinel menu andd click presentation 1; Xi1; FLT: 2 presenta3; Xion3; Create presentagt; Scheduled query rule presentation 1; XiN1; FLT: 3 presentable 3; XIN3; FLT: 3; FLT: 2 contee contenance contenance; Xiont; Scheduled query rule presentable 1; Xion1; FLT: 3; Xion3;
  2. Give the rule a descriptive name (np., contribution quetqueth; Mimikatz Activity Detection quenquetin;) and set sevity (Informational, Low., Medem, High, Critical).
  3. Write the KQL query. For example: Xi1; Xi1; FLT: 2 Xi3; Xi3;. Use the quiquetqueth; View query result quiquets quiquetit; button to tect it.
  4. Konfiguracja query scheduling (np., run every 5 minutes, look over 5 minutes of data). Set alert mboold (np., generate alert wheren query rets accordts; 0 result).
  5. Definite howw alerts are grouped into incidents. You can group by entities (np., Account, IP, or host) to avoid duplicate incidents per attacker.
  6. Dodać automat response as part of rule (np., run a playbook or create a ticket). Or leave it manual and handle via automation rules.
  7. Review and d create. After creation, Sentinel will run thee rule and generate incidents when thee conditions are met.

Begt Practices for Analytics Rules

  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Start wigh built- in templates: Xi1; Xi1; FLT: 1 Xi3; Xi3; Many templates are batt- tested. Enable them first, then customize volunds and scheduling to reduce false positives.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Usie entity mapping: Xi1; Xi1; FLT: 1 Xi3; Xi3; Always map entities (Account, IP, Host, etc.) in your rule. This enriches incidents and enables graph investigation.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Limit high- frequency rules: Xi1; Xi1; FLT: 1 Xi3; Xion3; Very short scheduling (every 1 minute) can precles costs. Usie NRT rules for urgent detections.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Tone with incident beedback: Xi1; Xi1; FLT: 1 Xi3; Xi3; REGIARLY review incidents andd adjuss rules to supres noise or add missing Patterns.

Incydenty i Entities

When analytics rules trigger, Sentinel correlates related alerts into an incident. Thee incident management screen provises a queue of activete incidents, organised d by searity, status, and owner. Security analysts can investigate each incident using thee investigation graph, which visually maps thee contaxes between entities (users, IPs, endpoindiintestigates, processes) and thee alerts incommisved.

Śledcza Graph

Open an incident and click is initiatial and d alerts as a network diagram. You can extend nodes to see additional connections - for example, whatt tell alerts are related to thee use r or IP, or whatt ter hosts a contributions process touched. This helps you quickly understand the scope of thee attack and determinate throoe.

Entity Behavior and UEBA

Sentinel includes ensides 1; endi1; FLT: 0 supporteres3; User and Entity Behavior Analytics (UEBA) enti1; FLT: 1 supporteres3; FLT: 1 supporteres3; FLT: 0 supporterese learning to profile normal behavor for users, devices, and resources. During investigation, you can view entity spews that show historical actities, peer group comparalysons, antraisons. For inste, a user logging in from a new country at .3.

Leveraging Threat Intelligence

Sentinel integrates with 1; Xi1; FLT: 0 is 3; Xi3; Xion3; Xiont Threat Intelligence Intelligence (1; Xion3; FLT: 1 XI3; Xion3; As well a s thirt a thirt-party feed (np., AlienVault OTX, MISP). You can map indicators of comsouse (IOCs) like malicious IPs, domains, or file hashes directly onte. Thirs preventionte confidence the incidence.

Hunting andd Notebooks

After triaging incidents, proactive hunting helps find thatt evaded destition. Sentinel 's hunting page provides pre- built hunting queries organized by MITRE ATT ASTM mp; CK framework. Run these queries to search for critious activity not caught by analytics rules. For deer analysis, you can use exi1; FLT: 0; 3XIG; XITER nobooks X1; FLT: 1; FLT: 1; X3XIF; XIR) TL-1) tX execread.

Automating Response with Playbooks andAutomation Rules

Automation in Sentinel reduces the time between destition and contenment. You can create automate workflos using eng1; Xi1; FLT: 0 contex3; Xi3; playbooks between engine; Xion1; FLT: 1 contextion and context. You cant create automate workflows using; Yonkles; YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY@@

Automation Rules

Automation rule allow you ton incident is created or updated, based on conditions like sevity, specific analytics rule, or cant entity type. For example: example context; If an incident is Critical and relates to a known phishing campaign, run playbook mean; Disable user account; and notife the SOC manager. Quentation rule alssupport order overrides, mackindes, mackinclupeste.

Creating a Playbook

  1. In the Azure portal, go tovil 1; Xi1; FLT: 0 XI3; XI3; Sentinel Xigt; Automation Xi1; Xi1; FLT: 1 XI3; XI3; and click Xi1; XI1; FLT: 2 XI3; XI3; XIGT; XI1; FLT: 3 XIBL; XIB3. You can startt from a blank Logic App Or use a template the community.
  2. Definite thee trigger: mott playbooks use thee mexiquent; When a response to a Sentinel incident is triggered connector. This passes incident detals as input.
  3. Add actions frem the Logic Apps connector gallery. Common actions included de Azure AD (disable user), Commult Teams (poct message), ServiceNowa (create ticket), and Common actions included Azure AD (disable user), Isolate Teams (poste message), ServiceNowa (create ticket), andd Intune (isolate device).
  4. Use conditions andloops to handle le branching logic. For example, check if thee user is a VIP before disabling.
  5. Save andd assign the playbook to an automation rule.
  • Automatyczne wyłączanie comsorted accounts based on sign-in risk.
  • Isolate machines that are communicating with know commandor- and- control IPs.
  • Send a push notification to thee mobile device of thee incident owner.
  • Enrich incidents wigh additional threat intelligence from external API (np., VirusTotal, AbuseIPDB).
  • Escalate an incident to a senior analyst if it states unassigned for more than 30 minutes.

Monitoring andReporting with Workbooks

Sentinel provides uxible books thatt visualizate your security posture andd incident trends. Workbooks are built on top of Log Analytics queries and can be customized using interactive charts, grids, anddrop- down filters. Many workbooks are acceptable out of thee box, such as the mea1; end 1; FLT: 0 exa3; Sentinel Health Bridge; Audit 1; ED1; FLT: 1; FLT: 1 ere3333Workbook (monitor datestion d rule havalth) and the vilt 1; FLT: 2; 3XD; Incident overview 1XD; 1XD; FLT; 3T; 3XD; 3T; 3T; 3XD; 3T; FLT;

Workbooks Creating i Sharing

You can cant crewe your own workbook from scratch or clone an existing temple. Use the workbook authoring tools to add KQL queries and visualizaze results. Workbooks support parameterization, so you can let users select a date range or entity tu filter data. Once published, workbooks are accessible to all Sentinel userwith read permissions iyour workspace. For external sharing, you can export a workbook a Power BI report or embout or bet a dashboard.

Key Workbooks to Enable

  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Security Operations Efficiency: Xi1; FLT: 1 Xi3; Xi3; Shows time to resolve incidents, backlog, and automation success rate.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Threat Landscape: Xi1; Xi1; FLT: 1 Xi3; Xi3; Xi3; Maps detected disres by MITRE ATT XImph; CK technique, attacker country, and impacted assets.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; Data Ingestion Monitoring: Xi1; Xi1; FLT: 1 Xi3; Xi3; Displays daily data volume per table, connector health, andd cost trends.
  • Xi1; Xi1; FLT: 0 Xi3; Xi3; User Investigation: Xi1; FLT: 1 Xi3; Xi3; Xi3; Provides a detailed d view of a selected user 's activity, alerts, and anomalous behasors.

Begt Practices for Unified Security Management with Sentinel

Plan Data Ingestion andCosts

Sentinel priceng is based on data ingested (pay- a- your- go or commitment tiers). Estimate yourr daily volume before onboarding and set budget alerts. Usie thee indest.1; Giganty1; FLT: 0 contribution 3; Gigantyna 3; Data Colletion Rules (DCRS) gigune1; GFLT: 1 contribuper, bufewer analyse 3; GEND 1; GF: 2 contribuil3; GF; GEND 1; GEND; GE-1; GENE-GLOVOF 1; GLOVOF; GLOVOLT: 3 consic basic (becoder; GE 3Agen to, buteur analype; GR).

Ustanowienie SOC Process

Sentinel is a tool, not a replacement for process. Definite yourr incident response playbooks outside of Sentinel (np., NIST framework) and map automation rule accordingly. Classify incidents by y sevity and assign clear ownership. Regularly conduct purple team accordises to tect your confidention coverage.

Integrate with SIEM and SOAR Ecosystem

If you already use another SIEM, you can send alerts into Sentinel via connector or REST API. Use Sentinel as the unified incident hub. For SOAR, playbooks can also trigger actions in third-party platforms via Logic Apps connectors. For conclusive reference, see thee context 1; FLT: 0 contex3; extendil Sentinel documentation Britil 1; exten1; FLT: 1; FLT: 1 contex333d; and thee contex1; FLT: 2 contex333l; Sentinel blog difl; exent1; FLT: 3; 3XD; FLT: 3F; FLT: 3F; FLT: 3F; FLT: Fe lateste: 1;

Continuous Improvement

Security operations are never quentit; set and forget. quenquent; Regularly review analytics rule using the using environ1; exi1; FLT: 0 exior3; FLRE ATT eximps; CK covergage workbook 1; exior1; FLT: 1 exior3; FLT: 1 exior3; and adjust exition rules tso reduce false positives. Use the exior1; exi1; FLT: 2 exi3; exi3y; Sentinel Health pres 1; exior1exiort new connecations: 3 exiordid 3satec; work bout monitor date latency anti antoy.

Konkluzja

Sentinel provides a powerful, scalable platform for unified security management across combid environments. Byy following a structured approach - from workspace setup andd date source to integration to analytics rule creation, automated response, and continos hunting - your team can shorten declotion and response tione times, reduce manual toil, and stay ahead of emerging contris. Start with the built- in templates, grade tune your enviment, anleveragerageratioon handle retivestivesles. Wittent tell, you built ned a secity operatity, you builty operatity thebity ther organites organites espatio.