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Optimizing Microsoft Sentinel (SIEM) Environment

In the ever-evolving landscape of cybersecurity, the importance of a well-optimized Sentinel Environment cannot be overstated. As threats continue to morph and adapt, security teams must engage in a continuous process of assessment and enhancement. In this blog, we'll delve into a comprehensive guide on optimizing your Sentinel Environment, focusing on identifying high-impact use cases, refining queries, and minimizing false positives.


Step 1: Identify High-Incident Generating Use Cases

Security operations often face a barrage of incidents, and prioritizing resources based on impact is crucial. Begin your assessment by identifying use cases that generate a high number of incidents. Analyze historical incident data to pinpoint these high-impact scenarios. This initial step lays the foundation for a targeted and efficient optimization process.



SecurityIncident

| where Status == 'Closed'

| extend label = tostring(Labels[0].labelName)

| summarize arg_max(TimeGenerated, Status, Severity, Owner, AdditionalData,CreatedTime, Title, Classification, ClassificationComment, ClassificationReason, ModifiedBy, label) by IncidentNumber

| extend Tactics = todynamic(AdditionalData.tactics)

| extend Owner = todynamic(Owner.assignedTo)

| extend Product = todynamic((parse_json(tostring(AdditionalData.alertProductNames))[0]))

| summarize count() by Title, label, Classification, ClassificationReason, ClassificationComment

| order by count_


Once high-incident generating use cases are identified, it's time to scrutinize the effectiveness of their queries.


Evaluate the detection accuracy and relevance of queries associated with these use cases. Consider real-world examples or case studies to illustrate how refining queries can significantly enhance overall effectiveness. A keen focus on query optimization sets the stage for a more resilient Sentinel Environment.


Review the classification of the closed incidents. Review the usecases whose incidents are mostly getting closed as "False Positives' , 'Benign Positives'. Evaluate the Classification reason. Lot of incidents get closed as "SuspiciousButExpected" or "IncorrectAlertLogic".


False positives can inundate security teams, leading to alert fatigue and potential oversight of genuine threats. Tackle this challenge head-on by identifying and disabling use cases with a high false positive rate. Implement strategies that involve continuous monitoring, feedback loops, and regular adjustments. A proactive approach to mitigating false positives enhances the efficiency of your Sentinel Environment.


Step 2: Auto Closure Analysis


Auto closure of incidents is a double-edged sword. While it can streamline security operations, it also raises questions about the efficacy of use cases. Conduct a thorough analysis of auto-closed incidents to understand their implications. Are incidents being closed too quickly? What impact does this have on incident response? Addressing these questions ensures that the auto closure feature contributes positively to your security posture.



SecurityIncident

| where Status == 'Closed'

| extend label = tostring(Labels[0].labelName)

| where label == 'AutoClosed'

| summarize arg_max(TimeGenerated, Status, Severity, Owner, AdditionalData,CreatedTime, Title, Classification, ClassificationComment, ClassificationReason, ModifiedBy, label) by IncidentNumber

| extend Tactics = todynamic(AdditionalData.tactics)

| extend Owner = todynamic(Owner.assignedTo)

| extend Product = todynamic((parse_json(tostring(AdditionalData.alertProductNames))[0]))

| summarize count() by Title, label, Classification, ClassificationReason, ClassificationComment

| order by count_


Step 3: Evaluate Use Cases Inactive for 3 Months

Not all use cases trigger incidents consistently. Evaluate use cases that have remained inactive for the last 3 months. Are their detection logics still sound, or is an adjustment needed? Understanding the reasons behind inactivity ensures that even seemingly dormant use cases play a vital role in specific threat landscapes.



SecurityIncident

| extend RuleId = tostring(RelatedAnalyticRuleIds[0])

| summarize LastIncidentTime = arg_max(CreatedTime, RuleId) by Title

| where LastIncidentTime <= ago(89d)



Conclusion

In conclusion, optimizing your Sentinel Environment is a multifaceted process that demands continuous attention and refinement. By following this comprehensive assessment guide, you lay the groundwork for a robust security infrastructure. Remember that cybersecurity is a dynamic field, and your approach to optimization should reflect this dynamism. Implement these steps, share your experiences, and let's collectively fortify our defenses against emerging threats.


Disclaimer

The content of this blog is prepared based on my personal experiences and insights, with assistance from ChatGPT. The views expressed are my own, and the approaches suggested are recommendations, acknowledging that there are various potential ways to optimize a Sentinel Environment. It's important to note that this blog does not represent the official stance or endorsement of my employer. Cybersecurity is a dynamic field, and the content provided here is intended for informational purposes. Readers are encouraged to consider their unique circumstances and consult with their own cybersecurity experts for tailored advice.

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