Module 2: Splunk Data Collection and Log Analysis:

• Collecting logs from various sources using Splunk Universal Forwarder
• Configuring data inputs and source types
• Analyzing logs and performing searches in Splunk

Lab:

• Splunk Data Collection and Log Analysis
• Lab Exercise: Configuring Splunk Universal Forwarder to collect logs from different sources.
• Lab Exercise: Analyzing log data in Splunk using search queries, filters, and data visualization.

Module 3: Splunk Query Language (SPL) and Advanced Searching:

• Introduction to SPL and its syntax
• Building complex queries and filters in Splunk
• Using statistical and analytical functions in SPL

Lab:

• Splunk Query Language (SPL) and Advanced Searching
• Lab Exercise: Building complex search queries using SPL syntax.
• Lab Exercise: Applying statistical and analytical functions in Splunk for advanced log analysis.

Module 4: Threat Hunting with Splunk:

• Leveraging Splunk for proactive threat hunting
• Developing and executing threat-hunting strategies using Splunk
• Utilizing Splunk advanced search techniques for threat hunting

Lab:

• Threat Hunting with Splunk
• Lab Exercise: Developing and executing threat hunting queries in Splunk.
• Lab Exercise: Analyzing threat intelligence data and correlating it with log data in Splunk.

Module 5: Splunk Security Apps and Add-ons:

• Overview of Splunk security apps and add-ons
• Installing and configuring Splunk Enterprise Security (ES)
• Exploring other security-focused Splunk apps and add-ons

Lab:

•  Splunk Security Apps and Add-ons
• Lab Exercise: Installing and configuring Splunk Enterprise Security (ES) app.
• Lab Exercise: Exploring and utilizing other security-focused Splunk apps and add-ons

Module 6: Incident Response with Splunk:

• Using Splunk for incident detection and triage
• Developing incident response workflows and playbooks in Splunk
• Investigating security incidents using Splunk features and data analysis

Lab:

• Incident Response with Splunk
• Lab Exercise: Creating incident response workflows and playbooks in Splunk.
• Lab Exercise: Investigating and responding to simulated security incidents using Splunk.

Module 7: Advanced Analytics and Machine Learning in Splunk:

• Applying machine learning algorithms in Splunk for anomaly detection
• Building and fine-tuning predictive models in Splunk
• Utilizing Splunk’s advanced analytics features for security operations

Lab:

• Advanced Analytics and Machine Learning in Splunk
• Lab Exercise: Applying machine learning algorithms in Splunk for anomaly detection.
• Lab Exercise: Building and fine-tuning predictive models using Splunk’s machine learning toolkit.

Module 8: Splunk SIEM Optimization and Best Practices:

• Troubleshooting common issues and optimizing Splunk performance
• Scalability considerations and distributed Splunk deployments
• Staying up-to-date with Splunk SIEM best practices and industry trends

Lab:

• Splunk SIEM Optimization and Best Practices
• Lab Exercise: Troubleshooting common issues and optimizing Splunk performance.
• Lab Exercise: Scaling a Splunk deployment and implementing best practices for SOC operations.