Azure Sentinel for SIEM - Step-by-Step Execution

Process Flow - Azure Sentinel for SIEM

Start: Connect Data Sources

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Collect Security Data

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Analyze with AI & Rules

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Detect Threats

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Investigate Alerts

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Respond with Automation

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End

Azure Sentinel collects security data, analyzes it to detect threats, helps investigate alerts, and automates responses.

Execution Sample

Azure

1. Connect data sources
2. Collect logs and events
3. Apply detection rules
4. Generate alerts
5. Investigate and respond

This sequence shows how Azure Sentinel processes security data step-by-step.

Process Table

Step	Action	Input	Output	Notes
1	Connect Data Sources	Cloud apps, servers, devices	Data connectors active	Ready to receive data
2	Collect Security Data	Logs and events from sources	Raw security data stored	Continuous data flow
3	Apply Detection Rules	Raw data	Alerts generated	Rules and AI detect threats
4	Generate Alerts	Detected suspicious activity	Alert list updated	Alerts ready for review
5	Investigate Alerts	Alert details	Investigation results	Analyst reviews context
6	Respond with Automation	Investigation outcome	Automated actions triggered	Playbooks run automatically
7	End	All alerts processed	Security posture improved	Cycle repeats continuously

💡 All alerts processed and responses triggered; system waits for new data.

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	After Step 6	Final
Data Connectors	Inactive	Active	Active	Active	Active	Active	Active	Active
Security Data	None	None	Collected	Collected	Collected	Collected	Collected	Collected
Alerts	None	None	None	Generated	Updated	Reviewed	Responded	Processed
Investigation Status	None	None	None	None	Pending	Completed	Completed	Completed
Automation Status	None	None	None	None	None	Triggered	Triggered	Triggered

Key Moments - 3 Insights

Why do we need to connect data sources first before collecting data?

Because without active data connectors (see Step 1 in execution_table), Azure Sentinel cannot receive any security data to analyze.

What happens if detection rules do not generate any alerts?

If no alerts are generated (Step 3), then there is no suspicious activity detected, so investigation and response steps do not run.

How does automation improve the response process?

Automation triggers playbooks automatically after investigation (Step 6), speeding up response and reducing manual work.

Visual Quiz - 3 Questions

Look at the execution_table, what is the output after Step 3?

A Raw security data stored

B Data connectors active

C Alerts generated

D Automated actions triggered

💡 Hint

Check the 'Output' column for Step 3 in the execution_table.

At which step does Azure Sentinel start automated responses?

A Step 6

B Step 4

C Step 5

D Step 7

💡 Hint

Look for 'Automated actions triggered' in the 'Output' column.

If data connectors remain inactive, what will happen to security data collection?

A Data will still be collected

B No data will be collected

C Alerts will be generated anyway

D Automation will trigger without data

💡 Hint

Refer to the 'Data Connectors' variable in variable_tracker after Step 1.

Concept Snapshot

Azure Sentinel is a cloud SIEM tool.
Connect data sources first to collect security logs.
Apply detection rules to find threats.
Investigate alerts and respond automatically.
Automate with playbooks to speed up security actions.

Full Transcript

Azure Sentinel works by first connecting to your cloud apps, servers, and devices to collect security data. Once connected, it continuously gathers logs and events. Then, it applies detection rules and AI to find suspicious activities and generate alerts. Security analysts investigate these alerts to understand the threats. Finally, automated playbooks respond to threats quickly, improving your security posture. This cycle repeats continuously to keep your environment safe.