SIEM and SOAR

Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) are critical for modern cloud and hybrid environments. This guide provides actionable steps, real-life examples, and best practices for designing and implementing SIEM and SOAR strategies on AWS, Azure, and GCP.

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What is SIEM?

A SIEM solution collects, aggregates, and analyzes logs and events from across your infrastructure (cloud, on-prem, SaaS). It detects threats, provides alerts, and supports compliance.

Popular SIEM Tools:

• Azure Sentinel (Microsoft Sentinel)

• AWS Security Hub & Amazon GuardDuty

• Google Chronicle

• Splunk, Elastic SIEM, IBM QRadar

Example: Azure Sentinel Setup

az sentinel workspace create --resource-group my-rg --workspace-name my-sentinel
az sentinel alert-rule create --workspace-name my-sentinel --rule-name suspicious-login --display-name "Suspicious Login" --enabled true

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What is SOAR?

A SOAR solution automates incident response workflows, integrates with SIEM, and enables rapid, consistent reactions to threats (e.g., isolating a VM, disabling a user, opening a ticket).

Popular SOAR Tools:

• Azure Logic Apps (integrated with Sentinel)

• AWS Lambda (triggered by Security Hub/CloudWatch events)

• Google Cloud Functions

• Splunk SOAR, Palo Alto Cortex XSOAR

Example: Automated Response with Azure Logic Apps

• Trigger: Sentinel detects a brute-force login

• Action: Logic App disables the user in Azure AD and notifies the SOC via Teams

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Step-by-Step: Designing a SIEM & SOAR Strategy

1. Define Requirements:

   • Compliance (PCI, ISO, HIPAA)

   • Cloud providers (AWS, Azure, GCP)

   • Data sources (VMs, containers, SaaS, firewalls)

2. Select Tools:

   • Choose SIEM/SOAR solutions that integrate with your cloud and on-prem resources

3. Centralize Log Collection:

   • Use native agents (Azure Monitor Agent, AWS CloudWatch Agent, GCP Ops Agent)

   • Forward logs to SIEM (Syslog, API, Event Hub)

4. Develop Detection Rules:

   • Use built-in and custom rules for threats (e.g., impossible travel, privilege escalation)

5. Automate Response:

   • Create playbooks for common incidents (disable user, quarantine VM, notify team)

6. Test and Tune:

   • Simulate incidents (red team, purple team)

   • Tune rules to reduce false positives

7. Monitor and Improve:

   • Review incidents, update playbooks, and document lessons learned

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Real-Life Example: Multi-Cloud SIEM & SOAR

• Logs from AWS CloudTrail, Azure Activity Log, and GCP Audit Log are forwarded to Splunk SIEM.

• Splunk detects a suspicious login from a new country.

• SOAR playbook triggers: disables the user in all three clouds, opens a Jira ticket, and notifies the SOC in Slack.

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Best Practices

• Centralize log collection for all environments

• Automate common responses to reduce mean time to respond (MTTR)

• Regularly review and update detection rules and playbooks

• Integrate with ticketing and communication tools (Jira, ServiceNow, Teams, Slack)

• Use LLMs (Copilot, Claude) to analyze logs and suggest response actions

Common Pitfalls

• Not forwarding all relevant logs (missed data sources)

• Excessive false positives due to untuned rules

• Manual response to repeatable incidents

• Lack of incident documentation and post-incident review

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References

• Microsoft Sentinel Documentation
• AWS Security Hub
• Google Chronicle SIEM
• Splunk SOAR
• Elastic SIEM