What is SIEM?
SIEM (security information and event management) is a centralized platform that collects, aggregates, and analyzes log data from across your IT infrastructure. Its core functions include real-time monitoring, correlation of security events, and alerting on suspicious activity.
SIEM provides visibility into networks, endpoints, cloud resources, and applications by ingesting logs from sources like AWS CloudTrail and GuardDuty, Azure Activity Logs and Microsoft Defender for Cloud, GCP Audit Logs and Security Command Center, Kubernetes audit logs, and application-layer events from containers and serverless functions.
However, traditional SIEM faces challenges including limited cloud-native context (like ephemeral resource lifecycles and dynamic permissions), alert fatigue from high false-positive rates, and significant analyst time required for rule tuning and manual investigation. Over time, SIEM evolved to address compliance use cases including centralized log retention and monitoring controls required by frameworks like PCI DSS (Requirement 10), ISO 27001 (A.12.4), and SOC 2 (CC7.2), in addition to threat detection capabilities. SIEM excels at historical analysis and forensic investigation after incidents occur.
Incident Response Plan Template
A quickstart guide to creating a powerful incident response plan - designed specifically for organizations with cloud-based deployments.
What is SOAR?
SOAR (security orchestration, automation, and response) is a platform that automates and orchestrates security operations through playbooks and workflows. It relies on three pillars: security orchestration for tool integration, automation for repetitive tasks, and response for incident handling.
SOAR ingests alerts from multiple sources, including SIEM, and executes predefined playbooks to handle them. Typical capabilities include case management, threat intelligence enrichment, and automated containment actions.
This approach materially reduces mean time to respond (MTTR) by eliminating manual steps in incident response. Organizations typically see response times drop from hours to minutes for routine incidents once playbooks are operational. Playbooks play a vital role in standardizing response procedures across security teams. Additionally, SOAR facilitates collaboration between security analysts through centralized case management.
Core differences between SIEM and SOAR
The main difference is that SIEM focuses on detection and visibility, while SOAR focuses on response and automation. SIEM collects and analyzes vast amounts of log data, whereas SOAR acts on processed alerts and findings.
SIEM generates alerts for human review, but SOAR executes automated actions and manages workflows. Operationally, SIEM answers "what happened and when," while SOAR answers "what should we do about it." SIEM integrates by aggregating data from security tools, while SOAR orchestrates actions across those same tools.
Skill requirements: SIEM requires log analysis expertise, whereas SOAR requires workflow design and automation knowledge.
Deployment complexity: SIEM demands extensive tuning and rule creation, while SOAR requires playbook development and testing.
Cost considerations: SIEM is often priced by data volume ingested, whereas SOAR is typically priced by automation capabilities or user seats.
How XDR Fits with SIEM and SOAR
XDR (Extended Detection and Response) focuses on collecting and correlating telemetry across endpoints, identities, networks, and cloud workloads to detect threats. Unlike SIEM, which aggregates all log types for broad visibility, XDR specializes in security-specific telemetry with built-in threat detection logic.
XDR platforms like Microsoft Defender XDR, Palo Alto Cortex XDR, and CrowdStrike Falcon typically feed high-fidelity alerts into SIEM for centralized visibility and compliance logging. These same alerts can trigger SOAR playbooks for automated response. Many organizations use XDR for deep threat detection in specific domains (endpoints, email, identity) while SIEM provides the centralized audit trail and SOAR handles cross-tool orchestration.
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Why SIEM and SOAR work better together
The natural workflow is that SIEM detects and generates alerts, and SOAR consumes those alerts to automate the response with many enterprises integrating SOAR with SIEM systems to create closed-loop workflows. This integration creates a closed-loop security operations process from detection through remediation.
SOAR reduces SIEM alert fatigue by automatically handling low-severity incidents. Conversely, SIEM provides the context and intelligence that makes SOAR playbooks more effective. Integration enables security teams to focus on strategic threats while automation handles routine incidents. Furthermore, SOAR actions create audit trails that feed back into SIEM for compliance and analysis.
Benefits of integrating SIEM with SOAR
Faster incident response: Automated workflows eliminate manual handoffs between detection and action.
Reduced analyst workload: Automation handles repetitive tasks like alert triage, data enrichment, and initial containment.
Consistent response procedures: Standardized playbooks ensure best practices are followed every time.
Improved threat intelligence utilization: The system automatically enriches alerts with context from multiple sources.
Enhanced compliance: You get audit trails through documented automated actions and complete incident timelines.
Better resource allocation: Experienced analysts are freed from routine tasks to focus on complex investigations.
Scalable security operations: The system can handle growing alert volumes without proportional staffing increases.
Measurable security metrics: Integrated dashboards show clear detection-to-resolution timelines.
Optimized SIEM costs: Cloud-native platforms that analyze security signals natively (posture, runtime threats, identity risks) before forwarding to SIEM reduce high-volume telemetry ingestion. Organizations typically see 30-50% reduction in SIEM data volume by offloading cloud-specific analysis while maintaining detection coverage and compliance logging requirements.
What is SIEM? The cloud-native security evolution
SIEM stands for Security Information and Event Management. It is a unified platform that combines Security Information Management (SIM) and Security Event Management (SEM).
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Key Metrics for SIEM and SOAR Success
Detection metrics (SIEM):
Mean time to detect (MTTD): Time from event occurrence to alert generation (target: <15 minutes for critical threats)
False positive rate: Percentage of alerts requiring no action (target: <10% for high-severity alerts)
Coverage breadth: Percentage of infrastructure generating security telemetry (target: 95%+ of production assets)
Log ingestion cost per GB: Total SIEM spend divided by data volume (benchmark: $1-3/GB for cloud-native platforms)
Response metrics (SOAR):
Mean time to respond (MTTR): Time from alert to containment action (target: <30 minutes for automated playbooks)
Automation rate: Percentage of incidents handled without human intervention (target: 60%+ for Tier 1 alerts)
Playbook success rate: Percentage of automated responses that resolve incidents correctly (target: 95%+)
Analyst time saved: Hours reclaimed from manual tasks per week (benchmark: 20-30 hours for teams handling 500+ alerts/week)
Integration metrics (SIEM + SOAR):
End-to-end resolution time: Detection through verified remediation (target: <1 hour for critical cloud exposures)
SIEM cost reduction: Percentage decrease in ingestion costs via selective forwarding (benchmark: 30-50% for cloud-native analysis offload)
SIEM and SOAR Compliance Benefits by Framework
PCI DSS (Payment Card Industry Data Security Standard):
SIEM addresses Requirement 10 (log all access to cardholder data, retain logs 90+ days)
SOAR supports Requirement 12.10 (incident response plan with documented procedures)
ISO 27001 (Information Security Management):
SIEM enables A.12.4.1 (event logging) and A.12.4.2 (protection of log information)
SOAR facilitates A.16.1.5 (response to information security incidents)
SOC 2 (Service Organization Control):
SIEM provides evidence for CC7.2 (system monitors detect anomalies)
SOAR demonstrates CC7.3 (security incidents are responded to in accordance with policies)
NIST Cybersecurity Framework:
SIEM supports Detect (DE.AE: Anomalies and Events, DE.CM: Continuous Monitoring)
SOAR enables Respond (RS.AN: Analysis, RS.MI: Mitigation, RS.RP: Response Planning)
HIPAA (Health Insurance Portability and Accountability Act):
SIEM addresses §164.308(a)(1)(ii)(D) (information system activity review)
SOAR supports §164.308(a)(6) (security incident procedures)
Implementation challenges and considerations
Data integration complexity is a major hurdle when connecting SIEM with multiple security tools and SOAR platforms. You also face playbook development challenges, including logic design, testing, and maintaining accuracy as threats evolve.
There is often a cultural shift required to move from manual security operations to automation-first approaches. This can reveal skill gap issues where teams need both security expertise and automation development capabilities. Change management is critical when introducing automated response that may impact production systems.
False positive risks are also real, as automated SOAR actions based on inaccurate SIEM alerts can cause operational disruption. Vendor lock-in concerns arise when SIEM and SOAR solutions come from different providers with limited integration. You must plan for ongoing maintenance requirements for rules, playbooks, and integrations as infrastructure evolves. Finally, cloud-native environments introduce additional complexity with dynamic resources and ephemeral workloads.
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SIEM and SOAR Implementation Roadmap
Phase 1: Inventory and prioritize (Weeks 1-2)
Document all security data sources: cloud APIs, network devices, endpoints, applications
Identify compliance requirements that mandate log retention (PCI DSS, HIPAA, SOC 2)
Prioritize high-value detections: privileged access, public exposures, lateral movement indicators
Phase 2: Deploy SIEM foundation (Weeks 3-6)
Configure log ingestion from prioritized sources (start with cloud control planes: AWS CloudTrail, Azure Activity Logs)
Build initial detection rules for critical threats: credential compromise, configuration changes, data exfiltration
Establish baseline alert volume and false positive rates
Phase 3: Pilot SOAR on low-risk workflows (Weeks 7-10)
Select 3-5 high-volume, low-risk alert types for automation (expired certificates, public S3 buckets, failed login attempts)
Build playbooks with human-in-the-loop approval gates for validation
Measure time savings and accuracy before expanding automation
Phase 4: Scale automation with guardrails (Weeks 11-16)
Expand playbooks to medium-risk scenarios with automated containment (disable compromised credentials, isolate suspicious instances)
Implement approval workflows for production-impacting actions
Create rollback procedures for automated changes
Phase 5: Integrate and optimize (Weeks 17-20)
Connect SOAR actions back to SIEM for closed-loop audit trails
Tune detection rules based on SOAR response outcomes
Identify opportunities to reduce SIEM ingestion via native cloud analysis
Phase 6: Measure and iterate (Ongoing)
Track MTTD, MTTR, automation rate, and cost per incident
Refine playbooks based on false positive rates and analyst feedback
Expand coverage to additional data sources and use cases quarterly
Modern cloud security requirements for SIEM and SOAR
Cloud-native architectures create unique detection and response challenges with ephemeral resources that appear and disappear in minutes. Effective cloud security requires platforms that model relationships between identities, configurations, data, and runtime behavior in a unified graph—enabling you to trace attack paths across dynamic infrastructure. Agentless API-based analysis provides this visibility without the operational overhead of deploying and managing agents across thousands of short-lived containers and serverless functions.
Traditional SIEM often struggles with cloud scale and dynamic infrastructure changes. Cloud security requires context beyond logs, including configuration data, identity permissions, and network topology. Unified visibility across multi-cloud environments and hybrid infrastructure is equally important.
Modern cloud threats like misconfigurations and excessive permissions require different detection approaches than traditional malware. Cloud-native SOAR must handle automated infrastructure changes and API-driven remediation. Cloud posture and configuration assessments increasingly leverage agentless API-based scanning, while runtime threat detection and endpoint protection often rely on lightweight agents or eBPF-based sensors for deeper visibility.
Threat Detection and Response : renforcez la sécurité de votre cloud
Découvrez les fondamentaux du Threat Detection and Response, les bonnes pratiques associées et les outils essentiels pour renforcer la sécurité de votre cloud face aux menaces émergentes.
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How Wiz transforms cloud threat detection and response
Wiz connects the dots between what's happening in your cloud and what you should do about it. We feed high-priority findings directly into your existing SIEM and SOAR platforms, so you can detect and respond faster without replacing your current tools.
Here's how it works: Wiz analyzes your cloud posture—misconfigurations, excessive permissions, vulnerabilities—and correlates that with runtime signals from lightweight eBPF sensors. When we detect active threats like cryptomining or lateral movement, you get the full story: what's compromised, who owns it, and how bad the blast radius could be.
SIEM Integration: We send context-rich cloud security events to platforms like Splunk, Microsoft Sentinel, Google Security Operations, and others. This helps you cut through alert noise by prioritizing what actually matters.
SOAR Integration: Wiz findings trigger automated response workflows in platforms like Cortex XSOAR, IBM QRadar SOAR, D3 Security, and Torq—so you can remediate risks without manual handoffs.
Beyond detection, Wiz maps every cloud resource back to the code, templates, and teams responsible for it. When remediation kicks off, the right developer gets a ticket with all the context they need to fix it at the source—not just patch the symptom.
The result? Your SOC spends less time chasing false positives and more time stopping real threats. Plus, by analyzing cloud signals natively, Wiz reduces what you send to your SIEM—cutting ingestion costs by 30-50% while keeping detection coverage intact.
Ready to see it in action? Request a demo and explore how Wiz Defend works in your environment.
Cloud-Native Incident Response
Learn why security operations teams rely on Wiz to help them proactively detect and respond to unfolding cloud threats.
