Visit This Web URL https://masterytrail.com/product/accredited-expert-level-ibm-qradar-incident-forensics-advanced-video-course Lesson 1: Advanced QRadar Incident Forensics Architecture and Deployment
1.1. Deep dive into QRIF component architecture and interactions
1.2. Sizing and scaling QRIF processors and packet capture appliances
1.3. High availability and disaster recovery for QRIF data
1.4. Understanding data flow and processing pipeline in QRIF
1.5. Integrating QRIF with distributed QRadar deployments
1.6. Performance tuning QRIF for large-scale investigations
1.7. Network tap and span port configuration best practices for QRIF
1.8. Storage considerations and optimization for forensic data
1.9. Monitoring QRIF health and performance metrics
1.10. Troubleshooting common QRIF deployment issues
Lesson 2: Advanced Data Acquisition and Preservation
2.1. حرب Advanced network packet capture strategies (full vs. selective)
2.2. Remote data acquisition techniques for distributed assets
2.3. Preserving volatile data for live investigations
2.4. Ensuring data integrity and chain of custody within QRIF
2.5. Handling encrypted traffic and SSL/TLS decryption for analysis
2.6. Acquiring data from cloud environments integrated with QRadar
2.7. Utilizing flow data for initial scope definition and targeted capture
2.8. Best practices for managing and retaining large volumes of forensic data
2.9. Scripting data acquisition tasks using QRadar capabilities
2.10. Validating data sources and ensuring their admissibility
Lesson 3: Deep Dive into QRIF Search and Filtering
3.1. Mastering the QRIF search interface and query language
3.2. Utilizing advanced search operators and boolean logic
3.3. Filtering forensic data by complex criteria (e.g., time, source/destination, protocols, keywords)
3.4. Leveraging saved searches and their optimization
3.5. Creating and using search groups for collaborative investigations
3.6. Understanding the indexing process and its impact on search performance
3.7. Searching within reconstructed files and documents
3.8. Identifying and searching on specific file types and content categories
3.9. Utilizing metadata for effective filtering and analysis
3.10. Troubleshooting search performance issues in QRIF
Lesson 4: Reconstructing Network Sessions and Communications
4.1. Understanding the process of reconstructing network sessions from packet captures
4.2. Analyzing reconstructed TCP and UDP streams
4.3. Reconstructing and analyzing common application protocols (HTTP, FTP, SMTP, etc.)
4.4. Handling fragmented packets and their impact on reconstruction
4.5. Identifying and reconstructing encrypted sessions (if decryption is possible)
4.6. Analyzing peer-to-peer communications within reconstructed data
4.7. Visualizing network session flows and timelines
4.8. Exporting reconstructed session data for external analysis
4.9. Troubleshooting session reconstruction issues
4.10. Using reconstructed sessions to understand attacker movements
Lesson 5: File Content Analysis and Reconstruction in QRIF
5.1. How QRIF extracts and reconstructs files from network traffic
5.2. Analyzing reconstructed documents, images, and multimedia files
5.3. Identifying hidden and obfuscated file content
5.4. Performing keyword searches within reconstructed file contents
5.5. Extracting metadata from reconstructed files
5.6. Handling password-protected and encrypted files found in traffic
5.7. Integrating external file analysis tools with QRIF output
5.8. Carving data from raw packet captures for specific file types
5.9. Understanding limitations of file reconstruction and potential data loss
5.10. Documenting findings related to reconstructed file evidence
Lesson 6: Advanced Log Source Analysis for Forensics
6.1. Correlating QRIF data with detailed event logs from various sources
6.2. Deep analysis of operating system logs for user activity and system changes
6.3. Investigating application logs for forensic artifacts
6.4. Analyzing security device logs (firewall, IPS, IDS) in conjunction with network data
6.5. Utilizing normalized and raw log data for comprehensive analysis
6.6. Creating custom log source extensions (DSMs) for unsupported data types
6.7. Leveraging AQL for complex log queries and forensic filtering
6.8. Identifying log manipulation and anti-forensic techniques
6.9. Integrating external log analysis tools with QRadar
6.10. Building forensic timelines based on correlated log events
Lesson 7: Flow Data Analysis for Forensic Investigations
7.1. Understanding the nuances of flow data (NetFlow, sFlow, J-Flow) in forensics
7.2. Analyzing flow records for network activity patterns and anomalies
7.3. Correlating flow data with packet captures for detailed analysis
7.4. Identifying suspicious network conversations and data exfiltration attempts via flow analysis
7.5. Utilizing QRadar Network Insights for enriched flow analysis
7.6. Customizing flow reporting and visualization for forensic purposes
7.7. Analyzing historical flow data for long-term investigations
7.8. Identifying network reconnaissance activities through flow analysis
7.9. Troubleshooting flow collection and processing issues impacting forensics
7.10. Using flow data to map network infrastructure and identify critical assets
Lesson 8: Correlating Events, Flows, and Packet Captures
8.1. Advanced techniques for correlating disparate data types in QRadar
8.2. Building complex correlation rules for forensic detection and alerting
8.3. Utilizing building blocks and reference sets for enhanced correlation
8.4. Analyzing offenses generated from forensic correlation rules
8.5. Tracing the kill chain through correlated event, flow, and packet data
8.6. Identifying lateral movement and internal reconnaissance using correlated data
8.7. Leveraging MITRE ATT&CK framework for correlating forensic findings
8.8. Tuning correlation rules to reduce false positives in forensic investigations
8.9. Visualizing correlated data using QRadar dashboards and apps
8.10. Documenting the correlation process and findings for reporting
Lesson 9: Incident Timeline Reconstruction
9.1. Methodologies for creating accurate and detailed incident timelines in QRadar
9.2. Utilizing QRIF's timeline visualization capabilities
9.3. Incorporating event logs, flow data, and packet capture artifacts into a single timeline
9.4. Synchronizing timelines across multiple data sources and systems
9.5. Identifying key events and milestones in an attack timeline
9.6. Analyzing temporal relationships between forensic artifacts
9.7. Handling time discrepancies and their impact on timeline accuracy
9.8. Exporting and presenting incident timelines
9.9. Using timelines to identify gaps in visibility and improve logging/monitoring
9.10. Reconstructing user activity timelines based on forensic evidence
Lesson 10: Investigating Insider Threats with QRadar Forensics
10.1. Identifying indicators of insider threat activity in QRadar data
10.2. Utilizing QRadar User Behavior Analytics (UBA) for insider threat detection
10.3. Analyzing user activity logs and network traffic for suspicious behavior
10.4. Investigating data exfiltration attempts by insiders
10.5. Reconstructing insider actions and motivations through forensic analysis
10.6. Correlating insider activity with policy violations and system misuse
10.7. Handling legal and privacy considerations in insider threat investigations
10.8. Building specific QRIF searches and filters for insider threat scenarios
10.9. Reporting on insider threat investigations and providing recommendations
10.10. Case studies of insider threat investigations using QRadar Forensics
Lesson 11: Malware Incident Forensics
11.1. Identifying malware-related artifacts in QRadar event and flow data
11.2. Analyzing network traffic generated by malware
11.3. Reconstructing malware droppers and command-and-control communications
11.4. Identifying compromised systems through forensic analysis
11.5. Integrating malware analysis platforms with QRadar
11.6. Utilizing threat intelligence feeds to identify known malware indicators
11.7. Searching for malware-specific patterns in reconstructed file content
11.8. Documenting malware analysis findings within the forensic report
11.9. Using QRIF to understand malware propagation and impact
11.10. Case studies of malware incident investigations using QRadar Forensics
Lesson 12: Investigating Cloud Incidents with QRadar Forensics
12.1. Challenges and considerations for cloud incident forensics
12.2. Integrating cloud service logs and flow data into QRadar
12.3. Analyzing activity within cloud environments (IaaS, PaaS, SaaS)
12.4. Identifying suspicious access and data movement in the cloud
12.5. Utilizing cloud provider APIs for forensic data acquisition
12.6. Correlating cloud events with on-premises data in QRadar
12.7. Investigating compromises of cloud accounts and services
12.8. Handling multi-cloud and hybrid cloud forensic scenarios
12.9. Reporting on cloud incident investigations
12.10. Case studies of cloud incident forensics using QRadar
Lesson 13: Advanced Network Forensic Artifact Analysis
13.1. Analyzing DNS requests and responses for malicious activity
13.2. Investigating HTTP headers and payloads for forensic clues
13.3. Analyzing SMB/CIFS traffic for file access and sharing
13.4. Examining email traffic (SMTP, POP3, IMAP) and attachments
13.5. Analyzing VoIP and real-time communication protocols
13.6. Identifying command and control (C2) channels in network traffic
13.7. Analyzing encrypted traffic for patterns and anomalies (even without decryption)
13.8. Utilizing BGP and routing information in network forensics
13.9. Investigating wireless network traffic for forensic artifacts
13.10. Analyzing industrial control system (ICS) network protocols (if applicable)
Lesson 14: Memory Forensics and QRadar Integration
14.1. Introduction to memory forensics concepts and techniques
14.2. Identifying scenarios where memory forensics is crucial
14.3. Integrating memory acquisition tools with QRadar workflows
14.4. Analyzing memory dumps for malicious processes, injected code, and artifacts
14.5. Correlating memory forensic findings with QRadar event and flow data
14.6. Utilizing QRadar to identify systems for memory acquisition
14.7. Automating memory acquisition and analysis tasks
14.8. Storing and managing memory forensic data within or alongside QRadar
14.9. Reporting on findings derived from memory analysis and QRadar correlation
14.10. Case studies demonstrating the value of memory forensics in QRadar investigations
Lesson 15: File System Forensics and QRadar Correlation
15.1. Introduction to file system forensic concepts (FAT, NTFS, Ext)
15.2. Identifying relevant file system artifacts for incident investigation
15.3. Integrating file system imaging and analysis tools with QRadar workflows
15.4. Analyzing file system metadata (timestamps, permissions, ownership)
15.5. Correlating file system events with QRadar logs and network activity
15.6. Utilizing QRadar to identify systems for file system acquisition
15.7. Searching for specific files and indicators of compromise (IOCs) on endpoints
15.8. Handling encrypted file systems and data recovery challenges
15.9. Reporting on findings derived from file system analysis and QRadar correlation
15.10. Case studies demonstrating the value of file system forensics in QRadar investigations
Lesson 16: Web Application Incident Forensics
16.1. Identifying web application attack indicators in QRadar data
16.2. Analyzing web server logs and application logs for forensic artifacts
16.3. Investigating HTTP requests and responses for malicious activity
16.4. Reconstructing web sessions and user interactions
16.5. Identifying SQL injection, cross-site scripting (XSS), and other web attacks
16.6. Utilizing QRadar to monitor web application traffic and identify anomalies
16.7. Correlating web attack events with backend system activity
16.8. Analyzing web server configurations and vulnerabilities
16.9. Reporting on web application incident investigations
16.10. Case studies of web application forensics using QRadar
Lesson 17: Database Incident Forensics
17.1. Identifying database attack indicators in QRadar data
17.2. Analyzing database audit logs and transaction logs
17.3. Investigating suspicious database queries and commands
17.4. Identifying data exfiltration from databases
17.5. Utilizing QRadar to monitor database traffic and identify anomalies
17.6. Correlating database events with application and network activity
17.7. Analyzing database configurations and vulnerabilities
17.8. Handling encrypted database traffic and data at rest
17.9. Reporting on database incident investigations
17.10. Case studies of database forensics using QRadar
Lesson 18: Email Incident Forensics
18.1. Identifying malicious email indicators in QRadar data (phishing, malware attachments)
18.2. Analyzing email server logs and gateway logs
18.3. Reconstructing email messages and analyzing headers
18.4. Extracting and analyzing email attachments within QRIF
18.5. Tracing email origins and delivery paths
18.6. Identifying compromised email accounts and their activity
18.7. Correlating email events with user activity and network traffic
18.8. Utilizing threat intelligence for identifying malicious email indicators
18.9. Reporting on email incident investigations
18.10. Case studies of email forensics using QRadar
Lesson 19: Mobile Device Forensics and QRadar Correlation
19.1. Challenges and considerations for mobile device forensics
19.2. Integrating mobile device management (MDM) logs into QRadar
19.3. Analyzing mobile device network traffic in QRadar
19.4. Correlating mobile device activity with user accounts and locations
19.5. Identifying compromised mobile devices and their impact
19.6. Utilizing QRadar to identify suspicious mobile application behavior
19.7. Incorporating mobile forensic findings into QRadar investigations
19.8. Handling legal and privacy aspects of mobile device forensics
19.9. Reporting on mobile device related incidents
19.10. Case studies involving mobile device forensics and QRadar
Lesson 20: SCADA/ICS Incident Forensics
20.1. Unique challenges of forensic investigations in SCADA/ICS environments
20.2. Integrating SCADA/ICS logs and network protocols into QRadar
20.3. Analyzing SCADA/ICS specific traffic and commands
20.4. Identifying malicious activity targeting industrial control systems
20.5. Correlating SCADA/ICS events with enterprise network activity
20.6. Utilizing QRadar to monitor critical infrastructure
20.7. Analyzing proprietary SCADA/ICS protocols (if applicable)
20.8. Handling offline and air-gapped SCADA/ICS systems
20.9. Reporting on SCADA/ICS incident investigations
20.10. Case studies of SCADA/ICS forensics using QRadar
Lesson 21: Integrating External Forensic Tools with QRadar
21.1. Identifying key external forensic tool categories (malware analysis, memory analysis, etc.)
21.2. Strategies for integrating external tool output into QRadar investigations
21.3. Utilizing QRadar's API for programmatic data exchange with external tools
21.4. Launching external tools from within the QRadar console (if supported)
21.5. Storing and referencing external forensic findings within QRadar
21.6. Automating the handover of data to external tools using QRadar SOAR
21.7. Visualizing integrated forensic data in QRadar dashboards
21.8. Managing data formats and compatibility between QRadar and external tools
21.9. Evaluating and selecting appropriate external tools for specific forensic tasks
21.10. Building a cohesive forensic toolchain around QRadar
Lesson 22: Advanced Threat Hunting with QRadar Forensics
22.1. Proactive threat hunting methodologies using QRadar data
22.2. Utilizing QRIF for deep dive analysis during threat hunting
22.3. Identifying undetected threats through anomaly detection in forensic data
22.4. Developing threat hunting hypotheses based on threat intelligence
22.5. Crafting advanced QRIF searches for specific threat behaviors
22.6. Leveraging historical forensic data for long-term threat analysis
22.7. Documenting threat hunting activities and findings within QRadar
22.8. Automating threat hunting tasks using QRadar capabilities
22.9. Collaborating on threat hunting investigations using QRadar features
22.10. Case studies of successful threat hunts using QRadar Forensics
Lesson 23: Customizing QRIF for Specific Investigations
23.1. Tailoring QRIF search views and dashboards for different investigation types
23.2. Creating custom content categories for specific data types
23.3. Developing custom parsing and indexing rules for unique data sources
23.4. Utilizing QRIF's API for custom scripting and automation
23.5. Integrating custom threat intelligence feeds into QRIF analysis
23.6. Configuring custom alerts and notifications based on forensic findings
23.7. Modifying QRIF's behavior through configuration files (with caution)
23.8. Developing custom reports for specific forensic requirements
23.9. Extending QRIF's capabilities with custom applications (if applicable)
23.10. Managing and deploying custom QRIF configurations
Lesson 24: Automating Forensic Workflows with QRadar API
24.1. Introduction to the QRadar API for forensic automation
24.2. Authenticating and interacting with the QRadar API
24.3. Programmatically triggering QRIF searches and recoveries
24.4. Extracting forensic data and metadata via the API
24.5. Updating offense data and adding forensic findings programmatically
24.6. Integrating QRIF with SOAR platforms for automated incident response
24.7. Developing scripts for repetitive forensic tasks
24.8. Error handling and logging in API-based forensic workflows
24.9. Security considerations when using the QRadar API for forensics
24.10. Building custom forensic dashboards and reports using API data
Lesson 25: Advanced AQL for Forensic Analysis
25.1. Mastering complex AQL queries for deep dive forensic analysis
25.2. Utilizing advanced AQL functions and operators
25.3. Joining data from different QRadar tables (events, flows, assets)
25.4. Performing statistical analysis of forensic data using AQL
25.5. Creating custom AQL functions for specific forensic calculations
25.6. Optimizing AQL queries for performance on large datasets
25.7. Using AQL within QRadar rules and searches for advanced filtering
25.8. Identifying complex patterns and anomalies with AQL
25.9. Exporting AQL query results for external analysis
25.10. Troubleshooting and debugging complex AQL queries
Lesson 26: Digital Impression and Entity Analysis
26.1. Understanding the concept and utility of Digital Impressions in QRIF
26.2. Analyzing relationships between entities (IPs, users, assets)
26.3. Identifying communication patterns and frequency
26.4. Mapping attacker infrastructure and pivot points
26.5. Utilizing digital impressions to uncover hidden connections
26.6. Correlating digital impression data with other forensic findings
26.7. Visualizing entity relationships and network graphs
26.8. Exporting digital impression data for external analysis
26.9. Troubleshooting digital impression generation
26.10. Using digital impressions to build a comprehensive picture of the incident
Lesson 27: Suspect Content Analysis and Categorization
27.1. How QRIF identifies and categorizes suspect content
27.2. Analyzing pre-defined suspect content categories
27.3. Creating custom rules for identifying specific suspect content
27.4. Searching and filtering based on suspect content categories
27.5. Investigating the context surrounding suspect content
27.6. Utilizing threat intelligence to inform suspect content rules
27.7. Handling false positives in suspect content identification
27.8. Documenting findings related to suspect content
27.9. Using suspect content analysis to prioritize investigations
27.10. Case studies involving suspect content analysis
Lesson 28: Advanced Reporting for Forensic Investigations
28.1. Designing comprehensive and legally defensible forensic reports in QRadar
28.2. Including key forensic findings and analysis in reports
28.3. Incorporating timelines, visualizations, and raw data exports
28.4. Customizing report templates for different stakeholders (technical, legal, management)
28.5. Automating report generation using QRadar capabilities and API
28.6. Ensuring report accuracy and completeness
28.7. Handling sensitive and confidential information in reports
28.8. Presenting forensic findings effectively in written and visual formats
28.9. Maintaining consistency and clarity in reporting language
28.10. Reviewing and validating forensic reports
Lesson 29: Legal Aspects of Digital Forensics with QRadar
29.1. Understanding legal requirements for digital evidence collection and handling
29.2. Maintaining chain of custody for forensic data in QRadar
29.3. Ensuring admissibility of QRadar data in legal proceedings
29.4. Handling privacy concerns and data protection regulations (e.g., GDPR, CCPA)
29.5. Working with legal counsel during forensic investigations
29.6. Preparing for potential expert testimony based on QRadar findings
29.7. Documenting all investigative steps for legal review
29.8. Understanding legal holds and their impact on QRadar data retention
29.9. Navigating cross-border legal considerations in investigations
29.10. Case studies involving legal challenges in digital forensics with SIEM data
Lesson 30: Preparing for Expert Testimony
30.1. Role and responsibilities of a forensic expert witness
30.2. Presenting complex technical findings to a non-technical audience
30.3. Preparing documentation and evidence for court
30.4. Handling cross-examination and challenging questions
30.5. Maintaining objectivity and impartiality
30.6. Communicating technical concepts clearly and concisely
30.7. Providing opinions based on forensic findings from QRadar
30.8. Understanding legal terminology and procedures
30.9. Practicing testimony and presentation skills
30.10. Case studies of expert testimony based on SIEM and forensic data
Lesson 31: Advanced Incident Response Playbooks with QRadar Forensics
31.1. Developing integrated incident response playbooks leveraging QRIF
31.2. Automating forensic data collection within playbooks
31.3. Utilizing Qradar SOAR for orchestrating forensic tasks
31.4. Incorporating threat intelligence and external tool integrations into playbooks
31.5. Defining roles and responsibilities for forensic activities in playbooks
31.6. Measuring the effectiveness of forensic playbooks
31.7. Continuous improvement of playbooks based on lessons learned
31.8. Handling different types of incidents with tailored forensic playbooks
31.9. Simulating incidents to test forensic response capabilities
31.10. Documenting and maintaining incident response playbooks
Lesson 32: Integrating Threat Intelligence into QRadar Forensics
32.1. Leveraging threat intelligence platforms (TIPs) with QRadar
32.2. Importing and managing threat intelligence feeds in QRadar
32.3. Correlating forensic findings with known IOCs and threat actor TTPs
32.4. Creating custom threat intelligence feeds for specific investigations
32.5. Utilizing threat intelligence to enrich QRIF search results
32.6. Automating threat intelligence lookups during forensic analysis
32.7. Sharing forensic findings as new threat intelligence
32.8. Evaluating the relevance and reliability of threat intelligence sources
32.9. Operationalizing threat intelligence for proactive forensics
32.10. Case studies demonstrating the value of threat intelligence in QRadar Forensics
Lesson 33: Advanced QRadar Administration for Forensics
33.1. Managing QRIF licenses and resource allocation
33.2. Configuring and optimizing QRIF system settings
33.3. Implementing access controls and user permissions for forensic data
33.4. Monitoring QRIF system health and troubleshooting performance bottlenecks
33.5. Performing backups and restores of QRIF data
33.6. Upgrading and patching QRIF components
33.7. Managing distributed QRIF deployments
33.8. Integrating QRIF with enterprise monitoring systems
33.9. Hardening QRIF appliances and infrastructure
33.10. Capacity planning for future forensic data storage and processing needs
Lesson 34: Troubleshooting Complex Forensic Scenarios
34.1. Identifying and resolving data collection issues impacting forensics
34.2. Troubleshooting packet capture and flow processing problems
34.3. Diagnosing issues with session reconstruction and file carving
34.4. Resolving search and filtering performance problems
34.5. Troubleshooting correlation rule logic impacting forensic alerts
34.6. Identifying and addressing data normalization issues
34.7. Debugging custom DSMs and parsing errors
34.8. Troubleshooting API integrations for forensic automation
34.9. Utilizing QRadar logs and diagnostic tools for forensics troubleshooting
34.10. Best practices for escalating complex QRIF issues to IBM support
Lesson 35: Future Trends in SIEM and Digital Forensics
35.1. The impact of artificial intelligence and machine learning on forensics
35.2. Cloud-native forensics challenges and solutions
35.3. Investigating incidents in ephemeral and containerized environments
35.4. The role of behavioral analytics in future forensic investigations
35.5. Automation and orchestration in the future of digital forensics
35.6. Emerging data sources and their relevance to forensics
35.7. Legal and ethical considerations in advanced digital forensics
35.8. The evolving threat landscape and its impact on forensic techniques
35.9. Integration of blockchain and distributed ledger technology in forensics
35.10. Preparing for future forensic challenges in a rapidly changing landscape
Lesson 36: Practical Forensic Investigation Walkthroughs (Case Studies 1)
36.1. Step-by-step investigation of a web application compromise
36.2. Utilizing QRIF to reconstruct the attack sequence
36.3. Analyzing relevant logs and network traffic
36.4. Identifying the initial point of compromise
36.5. Tracing attacker lateral movement
36.6. Analyzing extracted malware (if applicable)
36.7. Building the incident timeline
36.8. Documenting findings and generating a preliminary report
36.9. Identifying lessons learned and recommending remediation steps
36.10. Presenting the case study findings
Lesson 37: Practical Forensic Investigation Walkthroughs (Case Studies 2)
37.1. Step-by-step investigation of a data exfiltration incident
37.2. Utilizing QRIF to identify data transfer activities
37.3. Analyzing relevant logs and flow data
37.4. Identifying the source and destination of the data
37.5. Reconstructing the exfiltrated data (if possible)
37.6. Identifying the user or process responsible
37.7. Building the incident timeline
37.8. Documenting findings and generating a preliminary report
37.9. Identifying lessons learned and recommending remediation steps
37.10. Presenting the case study findings
Lesson 38: Practical Forensic Investigation Walkthroughs (Case Studies 3)
38.1. Step-by-step investigation of a suspected insider threat
38.2. Utilizing QRIF and UBA for insider activity analysis
38.3. Analyzing user logs and network traffic for suspicious behavior
38.4. Identifying policy violations and misuse of access
38.5. Reconstructing insider actions and motivations
38.6. Correlating activity with user identity and roles
37.7. Building the incident timeline
37.8. Documenting findings and generating a preliminary report
37.9. Identifying lessons learned and recommending remediation steps
37.10. Presenting the case study findings
Lesson 39: Advanced Techniques for Presenting Forensic Findings
39.1. Tailoring presentations for different audiences (technical, legal, executive)
39.2. Utilizing visualizations and diagrams to explain complex findings
39.3. Presenting technical evidence clearly and concisely
39.4. Handling questions and challenges during presentations
39.5. Focusing on the impact and significance of the findings
39.6. Using storytelling to present the incident narrative
39.7. Incorporating multimedia and interactive elements (if applicable)
39.8. Preparing executive summaries and technical appendices
39.9. Practicing presentation delivery and timing
39.10. Receiving and incorporating feedback on presentations
Lesson 40: Capstone: End-to-End Expert Forensic Investigation Simulation
40.1. Introduction to a complex, multi-stage simulated incident
40.2. Initial assessment and scoping of the investigation within QRadar
40.3. Developing a comprehensive forensic investigation plan
40.4. Executing advanced data acquisition and analysis techniques using QRIF
40.5. Correlating findings from various data sources
40.6. Reconstructing the full attack scenario and timeline
40.7. Utilizing external tools and threat intelligence for enrichment
40.8. Documenting all findings and preparing a detailed forensic report
4.9. Presenting the findings to a simulated executive/legal team