AI-Powered Cybersecurity Threat Hunting: Future-Proof Your Career and Stay Ahead of Automation
You’re not imagining it. The speed of change in cybersecurity is accelerating - and traditional threat detection methods are falling behind. Attackers evolve daily, using AI to bypass legacy defences. As a result, organisations are now prioritising professionals who can proactively hunt for threats, not just react to alerts. That’s where you come in. If you’ve ever felt uncertain about your career path, wondering whether your skills will remain relevant amid rising automation and intelligent attacks, this is your turning point. The AI-Powered Cybersecurity Threat Hunting: Future-Proof Your Career and Stay Ahead of Automation course is designed specifically for analysts, engineers, and IT leaders who are ready to lead in the new era of offensive security intelligence. This isn’t just theory. Within 30 days of starting, you’ll go from uncertainty to confidently building AI-augmented threat hunting frameworks that deliver measurable detection improvements. You’ll finish with a complete, board-ready implementation plan tailored to your environment - one that reduces breach risk and positions you as a strategic asset, not just a technical operator. Take Sarah M., Lead Security Analyst at a mid-sized financial services firm. After completing this program, she deployed an automated anomaly detection model that reduced mean time to detect threats by 68%. More importantly, she presented the results to the CISO with a fully documented use case, earning recognition and a promotion within two months. Organisations are no longer looking for people who patch systems. They want hunters. They want professionals who think like attackers, act like defenders, and use AI as a force multiplier. This course gives you the structured methodology, real-world tooling, and certification-backed credibility to make that shift - fast. Here’s how this course is structured to help you get there.Course Format & Delivery Details Designed for maximum flexibility, zero friction, and lifelong relevance - no matter your schedule or location. Self-Paced, On-Demand Access
This course is entirely self-paced, allowing you to learn at your own speed and on your own time. Once enrolled, you gain immediate access to the entire curriculum. There are no fixed start dates, no weekly deadlines, and no time zones to worry about. You decide when and where you learn - during commutes, after work, or in focused blocks over weekends. Most learners complete the core modules in 18–25 hours, with initial results visible in under a week. You can apply foundational techniques immediately, while building toward advanced implementation by the end. Lifetime Access & Continuous Updates
Your enrollment includes lifetime access to all course materials. As AI and cybersecurity evolve, so does this course. Every update - including new modules, tools, and threat patterns - is delivered automatically at no extra cost. Your skills stay current, and your investment keeps compounding long after completion. 24/7 Mobile-Friendly Learning Platform
Access everything from your phone, tablet, or laptop. The platform is engineered for performance and readability across devices, ensuring seamless progress whether you're on a train, in a coffee shop, or working remotely. Sync your progress across devices and never lose your place. Direct Instructor Support & Expert Guidance
You’re never alone. Throughout the course, you’ll have access to structured guidance from certified cybersecurity practitioners with real-world incident response and AI integration experience. This includes curated Q&A pathways, troubleshooting workflows, and direct feedback on key submissions to ensure your implementation aligns with enterprise-grade standards. Certificate of Completion from The Art of Service
Upon successful completion, you’ll receive a globally recognised Certificate of Completion issued by The Art of Service. This certification is referenced by hiring managers across Fortune 500 companies, government agencies, and top-tier MSSPs. It validates your ability to design and execute AI-driven threat hunting operations - a rare and high-value competency in today’s market. No Hidden Fees. Full Transparency.
The price you see is the price you pay - one flat fee with no hidden charges, no recurring subscriptions, and no upsells. You get full, permanent access to every resource, tool, and assessment in the program. - Accepted payment methods: Visa, Mastercard, PayPal
Unshakeable Risk Reversal: 30-Day Satisfied or Refunded
We stand behind the value of this course with a powerful promise: if you complete the first three modules and don’t believe your skills, clarity, and confidence have significantly improved, contact support for a full refund. No questions, no hassle. This is our commitment to delivering real ROI - not just promises. You Will Receive Confirmation and Access Separately
After enrollment, you’ll receive a confirmation email. Your access credentials and course entry instructions will be sent in a follow-up message once your enrolment is fully processed. This ensures data accuracy and secure account provisioning. This Works Even If…
You’re not a data scientist. You don’t have a PhD in machine learning. Your current role doesn’t involve AI. Your organisation hasn’t adopted advanced analytics yet. You’re worried your technical foundation isn’t strong enough. This program starts where you are. It’s been used successfully by SOC analysts, compliance officers, network engineers, and even non-technical IT managers who wanted to transition into high-impact security roles. The curriculum is role-agnostic in design but customisable in application - you apply every concept directly to your environment. Like James T., former Help Desk Supervisor at a healthcare provider, who used the framework in this course to build a low-code anomaly detection pipeline using existing SIEM data. He presented it to his IT director, earned a spot on the security task force, and transitioned into a full-time threat intelligence role within six months. This works because it’s not about knowing everything. It’s about having a repeatable, AI-powered hunting methodology - and that’s exactly what you’ll gain.
Module 1: Foundations of AI-Driven Threat Hunting - The evolving threat landscape and the failure of reactive security models
- Why traditional SIEM and EDR tools are no longer enough
- Defining proactive threat hunting vs alert triage
- Understanding lateral movement, dwell time, and stealth techniques
- Core principles of hypothesis-driven hunting
- Integrating attacker mindset into defender strategy
- Mapping MITRE ATT&CK to real-world campaigns
- Identifying high-risk assets and crown jewel protection
- Building a threat profile for your organisation
- Introduction to AI in security: Supervised vs unsupervised learning
- How AI detects patterns humans miss in log data
- Understanding false positives and model drift in detection systems
- Key data sources for effective hunting: logs, netflow, endpoints
- Differentiating between anomaly detection and signature-based rules
- Establishing a baseline for normal user and system behaviour
Module 2: Threat Intelligence Integration & AI Augmentation - Types of threat intelligence: strategic, tactical, operational, technical
- Integrating open-source and commercial threat feeds
- Automated IOC enrichment using API-driven platforms
- Using natural language processing to extract IOCs from reports
- Building custom threat intelligence dashboards
- AI classification of threat reports by relevance and severity
- Automating TTP mapping from unstructured text
- Correlating external threat data with internal telemetry
- Creating dynamic watchlists based on emerging threats
- Applying clustering algorithms to group related campaigns
- Using entity resolution to de-anonymise attacker infrastructure
- Scoring adversary confidence using probabilistic models
- Automated reporting of threat landscape shifts to stakeholders
- Developing early warning systems using predictive analytics
- Integrating cyber threat alliances and ISAC data securely
Module 3: Data Engineering for Threat Hunting - Designing a centralised data lake for security telemetry
- Normalising logs from heterogeneous sources
- Schema design for longitudinal threat analysis
- ETL pipelines for automated log ingestion
- Data retention policies aligned with detection needs
- Reducing noise through intelligent filtering and aggregation
- Handling high-volume streaming data with scalable architecture
- Enriching raw events with contextual metadata
- Automated geolocation tagging of IP addresses
- User and device attribution across domains and identities
- Sessionisation of user activity for behaviour modelling
- Feature engineering for machine learning models
- Time-series alignment for cross-system correlation
- Privacy-preserving data handling and anonymisation
- Encryption and access controls for sensitive datasets
Module 4: Machine Learning Fundamentals for Defenders - Supervised learning for malware classification
- Unsupervised learning for anomaly detection
- Semi-supervised models for low-label environments
- Clustering user behaviour into risk tiers
- Outlier detection in authentication logs
- Principal Component Analysis for dimensionality reduction
- Using Gaussian Mixture Models for baseline deviation
- Time-series forecasting for resource usage spikes
- Neural networks for detecting encrypted C2 traffic
- Decision trees for interpretability in high-stakes decisions
- Feature importance scoring for root cause analysis
- Avoiding overfitting in small sample scenarios
- Model validation using confusion matrices and ROC curves
- Threshold tuning to balance precision and recall
- Interpreting black-box models with SHAP and LIME
Module 5: AI-Powered Detection Engineering - From hypothesis to detection rule: a structured workflow
- Writing Sigma rules for multi-platform coverage
- Automating rule generation from MITRE ATT&CK
- Testing detection efficacy with simulated attacks
- Dynamic thresholding using adaptive baselines
- Correlating low-fidelity signals into high-confidence alerts
- Creating temporal chains of suspicious events
- Using sequence mining to detect multi-stage attacks
- Automated alert deduplication and grouping
- Reducing analyst fatigue through intelligent prioritisation
- Building confidence scores for each detection
- Integrating business context into alert severity
- Detecting privilege escalation via behavioural deviation
- Identifying data exfiltration patterns in network flows
- Flagging living-off-the-land binary usage
Module 6: Automated Threat Hunting Workflows - Designing repeatable hunting playbooks
- Automating hypothesis generation using trend analysis
- Scheduling regular hunts based on threat intelligence updates
- Automated data collection across endpoints and cloud environments
- Parallel execution of multiple hunting queries
- Scripting hunts using Python and Elasticsearch DSL
- Automated report generation with executive summaries
- Sending findings to ticketing and incident response systems
- Integrating with SOAR for response automation
- Creating feedback loops from hunt results to detection rules
- Version controlling hunting logic for auditability
- Standardising output formats for stakeholder readability
- Using templated investigations for common attack types
- Automating IOC extraction and dissemination
- Measuring hunt effectiveness using recall and precision metrics
Module 7: Behavioural Analytics & UEBA - Principles of User and Entity Behaviour Analytics (UEBA)
- Creating individualised user baselines
- Detecting compromised accounts through anomaly detection
- Modelling insider threat patterns
- Scoring risky user actions over time
- Identifying privilege abuse through access pattern shifts
- Analysing file access anomalies and data hoarding
- Detecting brute-force and password spraying attacks
- Monitoring for unusual login locations and times
- Linking multiple entities in complex attack graphs
- Visualising lateral movement across the network
- Mapping application usage deviations
- Tracking administrative command misuse
- Analysing PowerShell and command-line obfuscation
- Correlating endpoint process trees with network activity
Module 8: Cloud & Hybrid Environment Hunting - Key differences in cloud-native threat hunting
- Identifying misconfigured S3 buckets and IAM roles
- Monitoring AWS CloudTrail for suspicious API calls
- Detecting lateral movement in Azure AD
- Analysing Google Workspace logs for data leakage
- Tracking cross-cloud resource access attempts
- Detecting container breakout and pod escalation
- Monitoring Kubernetes audit logs for privilege abuse
- Investigating serverless function abuse
- Analysing cloud storage access patterns
- Tracking data egress from cloud environments
- Detecting persistence via Lambda triggers or Cloud Functions
- Using AI to prioritise cloud security findings
- Building detection logic for multi-cloud architectures
- Integrating CSPM data into threat hunting workflows
Module 9: Adversarial AI and Defender Countermeasures - Understanding how attackers use AI and ML
- Detecting AI-generated phishing content
- Identifying deepfake voice and video attacks
- Spotting automated credential stuffing with intelligent rotation
- Defending against model inversion and data extraction attacks
- Recognising adversarial examples that fool classifiers
- Monitoring for poisoning attacks on training data
- Detecting model stealing through query analysis
- Protecting internal ML systems from exploitation
- Implementing detection logic for GAN-generated malware
- Using defensive AI to detect AI-powered attacks
- Creating red team profiles for adversarial simulation
- Training models to recognise synthetic user behaviour
- Building watchdog systems for model integrity
- Establishing AI usage governance policies
Module 10: Incident Response Integration - Seamless handoff from hunting to incident response
- Automating evidence packaging for forensics
- Generating incident timelines from hunt findings
- Populating IR playbooks with enriched context
- Triggering containment actions based on confidence scores
- Integrating with ticketing systems like Jira and ServiceNow
- Using hunt results to update IR runbooks
- Creating executive summaries for breach communication
- Preserving chain of custody in digital evidence
- Analysing attacker dwell time and TTP coverage
- Conducting post-incident threat hunts for residual access
- Mapping attacker infrastructure for legal action
- Reporting mean time to detect and respond
- Improving response efficacy through feedback loops
- Demonstrating risk reduction to compliance teams
Module 11: Custom Tooling & Scripting for Scalability - Building reusable Python scripts for data collection
- Creating APIs to connect disjointed security tools
- Automating report generation with templated outputs
- Developing custom dashboards using Grafana and Kibana
- Designing CLI tools for internal SOC use
- Integrating with Slack and email for alert notification
- Scripting bulk IOC ingest and sweep operations
- Building lightweight detection validators
- Creating data visualisation tools for executive briefings
- Automating compliance checks using CIS benchmarks
- Developing audit trail analyzers for privilege changes
- Building file integrity monitors with hashing validation
- Scripting cross-platform forensic data collection
- Using Jupyter Notebooks for exploratory analysis
- Documenting and sharing tools across teams
Module 12: Advanced Threat Hunting Techniques - Hunting for fileless malware and memory-resident threats
- Detecting DNS tunneling and covert channels
- Analysing SSL/TLS certificate anomalies
- Investigating DGA-generated domain requests
- Tracking API key misuse and token abuse
- Identifying peer-to-peer command and control
- Analysing Windows registry persistence mechanisms
- Detecting WMI and PowerShell-based attacks
- Monitoring scheduled task creation and modification
- Investigating LSASS memory dumping attempts
- Analysing suspicious service installations
- Detecting rogue SSH key deployments
- Tracking unusual process injection techniques
- Identifying Golden Ticket and Silver Ticket usage
- Proactively hunting for zero-day indicators
Module 13: Metrics, Reporting & Stakeholder Communication - Measuring the ROI of threat hunting activities
- Calculating reduction in mean time to detect (MTTD)
- Tracking number of threats identified pre-breach
- Demonstrating risk reduction to executive leadership
- Creating visual reports for board-level review
- Translating technical findings into business impact
- Using KPIs to justify security budget increases
- Reporting on detection coverage across MITRE ATT&CK
- Tracking false positive reduction over time
- Measuring analyst efficiency gains
- Building executive dashboards with live data
- Presenting findings in non-technical language
- Structuring monthly threat landscape summaries
- Generating compliance-aligned risk reports
- Automating recurring compliance and audit reports
Module 14: Building Your AI-Driven Threat Hunting Program - Assessing organisational readiness for AI-powered hunting
- Securing executive sponsorship and budget approval
- Defining scope, team structure, and success criteria
- Integrating with existing SOC workflows
- Establishing regular hunting cadence and rotation
- Creating a knowledge base of past hunts and findings
- Developing internal training materials for team scaling
- Setting up feedback mechanisms for continuous improvement
- Conducting peer review of hunting hypotheses
- Implementing version control and documentation standards
- Planning for scalability across departments and regions
- Integrating with third-party MSSP or managed detection services
- Establishing metrics review meetings with leadership
- Creating a roadmap for AI model maturity advancement
- Designing a long-term skill development pathway
Module 15: Capstone Project & Certification - Selecting a high-impact threat scenario for your environment
- Developing a detailed hunting hypothesis with AI augmentation
- Collecting and preparing relevant telemetry data
- Executing a full threat hunt using learned methodologies
- Applying machine learning models to detect anomalies
- Generating a comprehensive technical report
- Creating an executive summary with business implications
- Proposing detection rule updates based on findings
- Recommending policy or configuration changes
- Presenting results using stakeholder-aligned messaging
- Submitting for expert review and feedback
- Revising and finalising the capstone package
- Documenting lessons learned and process improvements
- Earning your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn and professional profiles
- The evolving threat landscape and the failure of reactive security models
- Why traditional SIEM and EDR tools are no longer enough
- Defining proactive threat hunting vs alert triage
- Understanding lateral movement, dwell time, and stealth techniques
- Core principles of hypothesis-driven hunting
- Integrating attacker mindset into defender strategy
- Mapping MITRE ATT&CK to real-world campaigns
- Identifying high-risk assets and crown jewel protection
- Building a threat profile for your organisation
- Introduction to AI in security: Supervised vs unsupervised learning
- How AI detects patterns humans miss in log data
- Understanding false positives and model drift in detection systems
- Key data sources for effective hunting: logs, netflow, endpoints
- Differentiating between anomaly detection and signature-based rules
- Establishing a baseline for normal user and system behaviour
Module 2: Threat Intelligence Integration & AI Augmentation - Types of threat intelligence: strategic, tactical, operational, technical
- Integrating open-source and commercial threat feeds
- Automated IOC enrichment using API-driven platforms
- Using natural language processing to extract IOCs from reports
- Building custom threat intelligence dashboards
- AI classification of threat reports by relevance and severity
- Automating TTP mapping from unstructured text
- Correlating external threat data with internal telemetry
- Creating dynamic watchlists based on emerging threats
- Applying clustering algorithms to group related campaigns
- Using entity resolution to de-anonymise attacker infrastructure
- Scoring adversary confidence using probabilistic models
- Automated reporting of threat landscape shifts to stakeholders
- Developing early warning systems using predictive analytics
- Integrating cyber threat alliances and ISAC data securely
Module 3: Data Engineering for Threat Hunting - Designing a centralised data lake for security telemetry
- Normalising logs from heterogeneous sources
- Schema design for longitudinal threat analysis
- ETL pipelines for automated log ingestion
- Data retention policies aligned with detection needs
- Reducing noise through intelligent filtering and aggregation
- Handling high-volume streaming data with scalable architecture
- Enriching raw events with contextual metadata
- Automated geolocation tagging of IP addresses
- User and device attribution across domains and identities
- Sessionisation of user activity for behaviour modelling
- Feature engineering for machine learning models
- Time-series alignment for cross-system correlation
- Privacy-preserving data handling and anonymisation
- Encryption and access controls for sensitive datasets
Module 4: Machine Learning Fundamentals for Defenders - Supervised learning for malware classification
- Unsupervised learning for anomaly detection
- Semi-supervised models for low-label environments
- Clustering user behaviour into risk tiers
- Outlier detection in authentication logs
- Principal Component Analysis for dimensionality reduction
- Using Gaussian Mixture Models for baseline deviation
- Time-series forecasting for resource usage spikes
- Neural networks for detecting encrypted C2 traffic
- Decision trees for interpretability in high-stakes decisions
- Feature importance scoring for root cause analysis
- Avoiding overfitting in small sample scenarios
- Model validation using confusion matrices and ROC curves
- Threshold tuning to balance precision and recall
- Interpreting black-box models with SHAP and LIME
Module 5: AI-Powered Detection Engineering - From hypothesis to detection rule: a structured workflow
- Writing Sigma rules for multi-platform coverage
- Automating rule generation from MITRE ATT&CK
- Testing detection efficacy with simulated attacks
- Dynamic thresholding using adaptive baselines
- Correlating low-fidelity signals into high-confidence alerts
- Creating temporal chains of suspicious events
- Using sequence mining to detect multi-stage attacks
- Automated alert deduplication and grouping
- Reducing analyst fatigue through intelligent prioritisation
- Building confidence scores for each detection
- Integrating business context into alert severity
- Detecting privilege escalation via behavioural deviation
- Identifying data exfiltration patterns in network flows
- Flagging living-off-the-land binary usage
Module 6: Automated Threat Hunting Workflows - Designing repeatable hunting playbooks
- Automating hypothesis generation using trend analysis
- Scheduling regular hunts based on threat intelligence updates
- Automated data collection across endpoints and cloud environments
- Parallel execution of multiple hunting queries
- Scripting hunts using Python and Elasticsearch DSL
- Automated report generation with executive summaries
- Sending findings to ticketing and incident response systems
- Integrating with SOAR for response automation
- Creating feedback loops from hunt results to detection rules
- Version controlling hunting logic for auditability
- Standardising output formats for stakeholder readability
- Using templated investigations for common attack types
- Automating IOC extraction and dissemination
- Measuring hunt effectiveness using recall and precision metrics
Module 7: Behavioural Analytics & UEBA - Principles of User and Entity Behaviour Analytics (UEBA)
- Creating individualised user baselines
- Detecting compromised accounts through anomaly detection
- Modelling insider threat patterns
- Scoring risky user actions over time
- Identifying privilege abuse through access pattern shifts
- Analysing file access anomalies and data hoarding
- Detecting brute-force and password spraying attacks
- Monitoring for unusual login locations and times
- Linking multiple entities in complex attack graphs
- Visualising lateral movement across the network
- Mapping application usage deviations
- Tracking administrative command misuse
- Analysing PowerShell and command-line obfuscation
- Correlating endpoint process trees with network activity
Module 8: Cloud & Hybrid Environment Hunting - Key differences in cloud-native threat hunting
- Identifying misconfigured S3 buckets and IAM roles
- Monitoring AWS CloudTrail for suspicious API calls
- Detecting lateral movement in Azure AD
- Analysing Google Workspace logs for data leakage
- Tracking cross-cloud resource access attempts
- Detecting container breakout and pod escalation
- Monitoring Kubernetes audit logs for privilege abuse
- Investigating serverless function abuse
- Analysing cloud storage access patterns
- Tracking data egress from cloud environments
- Detecting persistence via Lambda triggers or Cloud Functions
- Using AI to prioritise cloud security findings
- Building detection logic for multi-cloud architectures
- Integrating CSPM data into threat hunting workflows
Module 9: Adversarial AI and Defender Countermeasures - Understanding how attackers use AI and ML
- Detecting AI-generated phishing content
- Identifying deepfake voice and video attacks
- Spotting automated credential stuffing with intelligent rotation
- Defending against model inversion and data extraction attacks
- Recognising adversarial examples that fool classifiers
- Monitoring for poisoning attacks on training data
- Detecting model stealing through query analysis
- Protecting internal ML systems from exploitation
- Implementing detection logic for GAN-generated malware
- Using defensive AI to detect AI-powered attacks
- Creating red team profiles for adversarial simulation
- Training models to recognise synthetic user behaviour
- Building watchdog systems for model integrity
- Establishing AI usage governance policies
Module 10: Incident Response Integration - Seamless handoff from hunting to incident response
- Automating evidence packaging for forensics
- Generating incident timelines from hunt findings
- Populating IR playbooks with enriched context
- Triggering containment actions based on confidence scores
- Integrating with ticketing systems like Jira and ServiceNow
- Using hunt results to update IR runbooks
- Creating executive summaries for breach communication
- Preserving chain of custody in digital evidence
- Analysing attacker dwell time and TTP coverage
- Conducting post-incident threat hunts for residual access
- Mapping attacker infrastructure for legal action
- Reporting mean time to detect and respond
- Improving response efficacy through feedback loops
- Demonstrating risk reduction to compliance teams
Module 11: Custom Tooling & Scripting for Scalability - Building reusable Python scripts for data collection
- Creating APIs to connect disjointed security tools
- Automating report generation with templated outputs
- Developing custom dashboards using Grafana and Kibana
- Designing CLI tools for internal SOC use
- Integrating with Slack and email for alert notification
- Scripting bulk IOC ingest and sweep operations
- Building lightweight detection validators
- Creating data visualisation tools for executive briefings
- Automating compliance checks using CIS benchmarks
- Developing audit trail analyzers for privilege changes
- Building file integrity monitors with hashing validation
- Scripting cross-platform forensic data collection
- Using Jupyter Notebooks for exploratory analysis
- Documenting and sharing tools across teams
Module 12: Advanced Threat Hunting Techniques - Hunting for fileless malware and memory-resident threats
- Detecting DNS tunneling and covert channels
- Analysing SSL/TLS certificate anomalies
- Investigating DGA-generated domain requests
- Tracking API key misuse and token abuse
- Identifying peer-to-peer command and control
- Analysing Windows registry persistence mechanisms
- Detecting WMI and PowerShell-based attacks
- Monitoring scheduled task creation and modification
- Investigating LSASS memory dumping attempts
- Analysing suspicious service installations
- Detecting rogue SSH key deployments
- Tracking unusual process injection techniques
- Identifying Golden Ticket and Silver Ticket usage
- Proactively hunting for zero-day indicators
Module 13: Metrics, Reporting & Stakeholder Communication - Measuring the ROI of threat hunting activities
- Calculating reduction in mean time to detect (MTTD)
- Tracking number of threats identified pre-breach
- Demonstrating risk reduction to executive leadership
- Creating visual reports for board-level review
- Translating technical findings into business impact
- Using KPIs to justify security budget increases
- Reporting on detection coverage across MITRE ATT&CK
- Tracking false positive reduction over time
- Measuring analyst efficiency gains
- Building executive dashboards with live data
- Presenting findings in non-technical language
- Structuring monthly threat landscape summaries
- Generating compliance-aligned risk reports
- Automating recurring compliance and audit reports
Module 14: Building Your AI-Driven Threat Hunting Program - Assessing organisational readiness for AI-powered hunting
- Securing executive sponsorship and budget approval
- Defining scope, team structure, and success criteria
- Integrating with existing SOC workflows
- Establishing regular hunting cadence and rotation
- Creating a knowledge base of past hunts and findings
- Developing internal training materials for team scaling
- Setting up feedback mechanisms for continuous improvement
- Conducting peer review of hunting hypotheses
- Implementing version control and documentation standards
- Planning for scalability across departments and regions
- Integrating with third-party MSSP or managed detection services
- Establishing metrics review meetings with leadership
- Creating a roadmap for AI model maturity advancement
- Designing a long-term skill development pathway
Module 15: Capstone Project & Certification - Selecting a high-impact threat scenario for your environment
- Developing a detailed hunting hypothesis with AI augmentation
- Collecting and preparing relevant telemetry data
- Executing a full threat hunt using learned methodologies
- Applying machine learning models to detect anomalies
- Generating a comprehensive technical report
- Creating an executive summary with business implications
- Proposing detection rule updates based on findings
- Recommending policy or configuration changes
- Presenting results using stakeholder-aligned messaging
- Submitting for expert review and feedback
- Revising and finalising the capstone package
- Documenting lessons learned and process improvements
- Earning your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn and professional profiles
- Designing a centralised data lake for security telemetry
- Normalising logs from heterogeneous sources
- Schema design for longitudinal threat analysis
- ETL pipelines for automated log ingestion
- Data retention policies aligned with detection needs
- Reducing noise through intelligent filtering and aggregation
- Handling high-volume streaming data with scalable architecture
- Enriching raw events with contextual metadata
- Automated geolocation tagging of IP addresses
- User and device attribution across domains and identities
- Sessionisation of user activity for behaviour modelling
- Feature engineering for machine learning models
- Time-series alignment for cross-system correlation
- Privacy-preserving data handling and anonymisation
- Encryption and access controls for sensitive datasets
Module 4: Machine Learning Fundamentals for Defenders - Supervised learning for malware classification
- Unsupervised learning for anomaly detection
- Semi-supervised models for low-label environments
- Clustering user behaviour into risk tiers
- Outlier detection in authentication logs
- Principal Component Analysis for dimensionality reduction
- Using Gaussian Mixture Models for baseline deviation
- Time-series forecasting for resource usage spikes
- Neural networks for detecting encrypted C2 traffic
- Decision trees for interpretability in high-stakes decisions
- Feature importance scoring for root cause analysis
- Avoiding overfitting in small sample scenarios
- Model validation using confusion matrices and ROC curves
- Threshold tuning to balance precision and recall
- Interpreting black-box models with SHAP and LIME
Module 5: AI-Powered Detection Engineering - From hypothesis to detection rule: a structured workflow
- Writing Sigma rules for multi-platform coverage
- Automating rule generation from MITRE ATT&CK
- Testing detection efficacy with simulated attacks
- Dynamic thresholding using adaptive baselines
- Correlating low-fidelity signals into high-confidence alerts
- Creating temporal chains of suspicious events
- Using sequence mining to detect multi-stage attacks
- Automated alert deduplication and grouping
- Reducing analyst fatigue through intelligent prioritisation
- Building confidence scores for each detection
- Integrating business context into alert severity
- Detecting privilege escalation via behavioural deviation
- Identifying data exfiltration patterns in network flows
- Flagging living-off-the-land binary usage
Module 6: Automated Threat Hunting Workflows - Designing repeatable hunting playbooks
- Automating hypothesis generation using trend analysis
- Scheduling regular hunts based on threat intelligence updates
- Automated data collection across endpoints and cloud environments
- Parallel execution of multiple hunting queries
- Scripting hunts using Python and Elasticsearch DSL
- Automated report generation with executive summaries
- Sending findings to ticketing and incident response systems
- Integrating with SOAR for response automation
- Creating feedback loops from hunt results to detection rules
- Version controlling hunting logic for auditability
- Standardising output formats for stakeholder readability
- Using templated investigations for common attack types
- Automating IOC extraction and dissemination
- Measuring hunt effectiveness using recall and precision metrics
Module 7: Behavioural Analytics & UEBA - Principles of User and Entity Behaviour Analytics (UEBA)
- Creating individualised user baselines
- Detecting compromised accounts through anomaly detection
- Modelling insider threat patterns
- Scoring risky user actions over time
- Identifying privilege abuse through access pattern shifts
- Analysing file access anomalies and data hoarding
- Detecting brute-force and password spraying attacks
- Monitoring for unusual login locations and times
- Linking multiple entities in complex attack graphs
- Visualising lateral movement across the network
- Mapping application usage deviations
- Tracking administrative command misuse
- Analysing PowerShell and command-line obfuscation
- Correlating endpoint process trees with network activity
Module 8: Cloud & Hybrid Environment Hunting - Key differences in cloud-native threat hunting
- Identifying misconfigured S3 buckets and IAM roles
- Monitoring AWS CloudTrail for suspicious API calls
- Detecting lateral movement in Azure AD
- Analysing Google Workspace logs for data leakage
- Tracking cross-cloud resource access attempts
- Detecting container breakout and pod escalation
- Monitoring Kubernetes audit logs for privilege abuse
- Investigating serverless function abuse
- Analysing cloud storage access patterns
- Tracking data egress from cloud environments
- Detecting persistence via Lambda triggers or Cloud Functions
- Using AI to prioritise cloud security findings
- Building detection logic for multi-cloud architectures
- Integrating CSPM data into threat hunting workflows
Module 9: Adversarial AI and Defender Countermeasures - Understanding how attackers use AI and ML
- Detecting AI-generated phishing content
- Identifying deepfake voice and video attacks
- Spotting automated credential stuffing with intelligent rotation
- Defending against model inversion and data extraction attacks
- Recognising adversarial examples that fool classifiers
- Monitoring for poisoning attacks on training data
- Detecting model stealing through query analysis
- Protecting internal ML systems from exploitation
- Implementing detection logic for GAN-generated malware
- Using defensive AI to detect AI-powered attacks
- Creating red team profiles for adversarial simulation
- Training models to recognise synthetic user behaviour
- Building watchdog systems for model integrity
- Establishing AI usage governance policies
Module 10: Incident Response Integration - Seamless handoff from hunting to incident response
- Automating evidence packaging for forensics
- Generating incident timelines from hunt findings
- Populating IR playbooks with enriched context
- Triggering containment actions based on confidence scores
- Integrating with ticketing systems like Jira and ServiceNow
- Using hunt results to update IR runbooks
- Creating executive summaries for breach communication
- Preserving chain of custody in digital evidence
- Analysing attacker dwell time and TTP coverage
- Conducting post-incident threat hunts for residual access
- Mapping attacker infrastructure for legal action
- Reporting mean time to detect and respond
- Improving response efficacy through feedback loops
- Demonstrating risk reduction to compliance teams
Module 11: Custom Tooling & Scripting for Scalability - Building reusable Python scripts for data collection
- Creating APIs to connect disjointed security tools
- Automating report generation with templated outputs
- Developing custom dashboards using Grafana and Kibana
- Designing CLI tools for internal SOC use
- Integrating with Slack and email for alert notification
- Scripting bulk IOC ingest and sweep operations
- Building lightweight detection validators
- Creating data visualisation tools for executive briefings
- Automating compliance checks using CIS benchmarks
- Developing audit trail analyzers for privilege changes
- Building file integrity monitors with hashing validation
- Scripting cross-platform forensic data collection
- Using Jupyter Notebooks for exploratory analysis
- Documenting and sharing tools across teams
Module 12: Advanced Threat Hunting Techniques - Hunting for fileless malware and memory-resident threats
- Detecting DNS tunneling and covert channels
- Analysing SSL/TLS certificate anomalies
- Investigating DGA-generated domain requests
- Tracking API key misuse and token abuse
- Identifying peer-to-peer command and control
- Analysing Windows registry persistence mechanisms
- Detecting WMI and PowerShell-based attacks
- Monitoring scheduled task creation and modification
- Investigating LSASS memory dumping attempts
- Analysing suspicious service installations
- Detecting rogue SSH key deployments
- Tracking unusual process injection techniques
- Identifying Golden Ticket and Silver Ticket usage
- Proactively hunting for zero-day indicators
Module 13: Metrics, Reporting & Stakeholder Communication - Measuring the ROI of threat hunting activities
- Calculating reduction in mean time to detect (MTTD)
- Tracking number of threats identified pre-breach
- Demonstrating risk reduction to executive leadership
- Creating visual reports for board-level review
- Translating technical findings into business impact
- Using KPIs to justify security budget increases
- Reporting on detection coverage across MITRE ATT&CK
- Tracking false positive reduction over time
- Measuring analyst efficiency gains
- Building executive dashboards with live data
- Presenting findings in non-technical language
- Structuring monthly threat landscape summaries
- Generating compliance-aligned risk reports
- Automating recurring compliance and audit reports
Module 14: Building Your AI-Driven Threat Hunting Program - Assessing organisational readiness for AI-powered hunting
- Securing executive sponsorship and budget approval
- Defining scope, team structure, and success criteria
- Integrating with existing SOC workflows
- Establishing regular hunting cadence and rotation
- Creating a knowledge base of past hunts and findings
- Developing internal training materials for team scaling
- Setting up feedback mechanisms for continuous improvement
- Conducting peer review of hunting hypotheses
- Implementing version control and documentation standards
- Planning for scalability across departments and regions
- Integrating with third-party MSSP or managed detection services
- Establishing metrics review meetings with leadership
- Creating a roadmap for AI model maturity advancement
- Designing a long-term skill development pathway
Module 15: Capstone Project & Certification - Selecting a high-impact threat scenario for your environment
- Developing a detailed hunting hypothesis with AI augmentation
- Collecting and preparing relevant telemetry data
- Executing a full threat hunt using learned methodologies
- Applying machine learning models to detect anomalies
- Generating a comprehensive technical report
- Creating an executive summary with business implications
- Proposing detection rule updates based on findings
- Recommending policy or configuration changes
- Presenting results using stakeholder-aligned messaging
- Submitting for expert review and feedback
- Revising and finalising the capstone package
- Documenting lessons learned and process improvements
- Earning your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn and professional profiles
- From hypothesis to detection rule: a structured workflow
- Writing Sigma rules for multi-platform coverage
- Automating rule generation from MITRE ATT&CK
- Testing detection efficacy with simulated attacks
- Dynamic thresholding using adaptive baselines
- Correlating low-fidelity signals into high-confidence alerts
- Creating temporal chains of suspicious events
- Using sequence mining to detect multi-stage attacks
- Automated alert deduplication and grouping
- Reducing analyst fatigue through intelligent prioritisation
- Building confidence scores for each detection
- Integrating business context into alert severity
- Detecting privilege escalation via behavioural deviation
- Identifying data exfiltration patterns in network flows
- Flagging living-off-the-land binary usage
Module 6: Automated Threat Hunting Workflows - Designing repeatable hunting playbooks
- Automating hypothesis generation using trend analysis
- Scheduling regular hunts based on threat intelligence updates
- Automated data collection across endpoints and cloud environments
- Parallel execution of multiple hunting queries
- Scripting hunts using Python and Elasticsearch DSL
- Automated report generation with executive summaries
- Sending findings to ticketing and incident response systems
- Integrating with SOAR for response automation
- Creating feedback loops from hunt results to detection rules
- Version controlling hunting logic for auditability
- Standardising output formats for stakeholder readability
- Using templated investigations for common attack types
- Automating IOC extraction and dissemination
- Measuring hunt effectiveness using recall and precision metrics
Module 7: Behavioural Analytics & UEBA - Principles of User and Entity Behaviour Analytics (UEBA)
- Creating individualised user baselines
- Detecting compromised accounts through anomaly detection
- Modelling insider threat patterns
- Scoring risky user actions over time
- Identifying privilege abuse through access pattern shifts
- Analysing file access anomalies and data hoarding
- Detecting brute-force and password spraying attacks
- Monitoring for unusual login locations and times
- Linking multiple entities in complex attack graphs
- Visualising lateral movement across the network
- Mapping application usage deviations
- Tracking administrative command misuse
- Analysing PowerShell and command-line obfuscation
- Correlating endpoint process trees with network activity
Module 8: Cloud & Hybrid Environment Hunting - Key differences in cloud-native threat hunting
- Identifying misconfigured S3 buckets and IAM roles
- Monitoring AWS CloudTrail for suspicious API calls
- Detecting lateral movement in Azure AD
- Analysing Google Workspace logs for data leakage
- Tracking cross-cloud resource access attempts
- Detecting container breakout and pod escalation
- Monitoring Kubernetes audit logs for privilege abuse
- Investigating serverless function abuse
- Analysing cloud storage access patterns
- Tracking data egress from cloud environments
- Detecting persistence via Lambda triggers or Cloud Functions
- Using AI to prioritise cloud security findings
- Building detection logic for multi-cloud architectures
- Integrating CSPM data into threat hunting workflows
Module 9: Adversarial AI and Defender Countermeasures - Understanding how attackers use AI and ML
- Detecting AI-generated phishing content
- Identifying deepfake voice and video attacks
- Spotting automated credential stuffing with intelligent rotation
- Defending against model inversion and data extraction attacks
- Recognising adversarial examples that fool classifiers
- Monitoring for poisoning attacks on training data
- Detecting model stealing through query analysis
- Protecting internal ML systems from exploitation
- Implementing detection logic for GAN-generated malware
- Using defensive AI to detect AI-powered attacks
- Creating red team profiles for adversarial simulation
- Training models to recognise synthetic user behaviour
- Building watchdog systems for model integrity
- Establishing AI usage governance policies
Module 10: Incident Response Integration - Seamless handoff from hunting to incident response
- Automating evidence packaging for forensics
- Generating incident timelines from hunt findings
- Populating IR playbooks with enriched context
- Triggering containment actions based on confidence scores
- Integrating with ticketing systems like Jira and ServiceNow
- Using hunt results to update IR runbooks
- Creating executive summaries for breach communication
- Preserving chain of custody in digital evidence
- Analysing attacker dwell time and TTP coverage
- Conducting post-incident threat hunts for residual access
- Mapping attacker infrastructure for legal action
- Reporting mean time to detect and respond
- Improving response efficacy through feedback loops
- Demonstrating risk reduction to compliance teams
Module 11: Custom Tooling & Scripting for Scalability - Building reusable Python scripts for data collection
- Creating APIs to connect disjointed security tools
- Automating report generation with templated outputs
- Developing custom dashboards using Grafana and Kibana
- Designing CLI tools for internal SOC use
- Integrating with Slack and email for alert notification
- Scripting bulk IOC ingest and sweep operations
- Building lightweight detection validators
- Creating data visualisation tools for executive briefings
- Automating compliance checks using CIS benchmarks
- Developing audit trail analyzers for privilege changes
- Building file integrity monitors with hashing validation
- Scripting cross-platform forensic data collection
- Using Jupyter Notebooks for exploratory analysis
- Documenting and sharing tools across teams
Module 12: Advanced Threat Hunting Techniques - Hunting for fileless malware and memory-resident threats
- Detecting DNS tunneling and covert channels
- Analysing SSL/TLS certificate anomalies
- Investigating DGA-generated domain requests
- Tracking API key misuse and token abuse
- Identifying peer-to-peer command and control
- Analysing Windows registry persistence mechanisms
- Detecting WMI and PowerShell-based attacks
- Monitoring scheduled task creation and modification
- Investigating LSASS memory dumping attempts
- Analysing suspicious service installations
- Detecting rogue SSH key deployments
- Tracking unusual process injection techniques
- Identifying Golden Ticket and Silver Ticket usage
- Proactively hunting for zero-day indicators
Module 13: Metrics, Reporting & Stakeholder Communication - Measuring the ROI of threat hunting activities
- Calculating reduction in mean time to detect (MTTD)
- Tracking number of threats identified pre-breach
- Demonstrating risk reduction to executive leadership
- Creating visual reports for board-level review
- Translating technical findings into business impact
- Using KPIs to justify security budget increases
- Reporting on detection coverage across MITRE ATT&CK
- Tracking false positive reduction over time
- Measuring analyst efficiency gains
- Building executive dashboards with live data
- Presenting findings in non-technical language
- Structuring monthly threat landscape summaries
- Generating compliance-aligned risk reports
- Automating recurring compliance and audit reports
Module 14: Building Your AI-Driven Threat Hunting Program - Assessing organisational readiness for AI-powered hunting
- Securing executive sponsorship and budget approval
- Defining scope, team structure, and success criteria
- Integrating with existing SOC workflows
- Establishing regular hunting cadence and rotation
- Creating a knowledge base of past hunts and findings
- Developing internal training materials for team scaling
- Setting up feedback mechanisms for continuous improvement
- Conducting peer review of hunting hypotheses
- Implementing version control and documentation standards
- Planning for scalability across departments and regions
- Integrating with third-party MSSP or managed detection services
- Establishing metrics review meetings with leadership
- Creating a roadmap for AI model maturity advancement
- Designing a long-term skill development pathway
Module 15: Capstone Project & Certification - Selecting a high-impact threat scenario for your environment
- Developing a detailed hunting hypothesis with AI augmentation
- Collecting and preparing relevant telemetry data
- Executing a full threat hunt using learned methodologies
- Applying machine learning models to detect anomalies
- Generating a comprehensive technical report
- Creating an executive summary with business implications
- Proposing detection rule updates based on findings
- Recommending policy or configuration changes
- Presenting results using stakeholder-aligned messaging
- Submitting for expert review and feedback
- Revising and finalising the capstone package
- Documenting lessons learned and process improvements
- Earning your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn and professional profiles
- Principles of User and Entity Behaviour Analytics (UEBA)
- Creating individualised user baselines
- Detecting compromised accounts through anomaly detection
- Modelling insider threat patterns
- Scoring risky user actions over time
- Identifying privilege abuse through access pattern shifts
- Analysing file access anomalies and data hoarding
- Detecting brute-force and password spraying attacks
- Monitoring for unusual login locations and times
- Linking multiple entities in complex attack graphs
- Visualising lateral movement across the network
- Mapping application usage deviations
- Tracking administrative command misuse
- Analysing PowerShell and command-line obfuscation
- Correlating endpoint process trees with network activity
Module 8: Cloud & Hybrid Environment Hunting - Key differences in cloud-native threat hunting
- Identifying misconfigured S3 buckets and IAM roles
- Monitoring AWS CloudTrail for suspicious API calls
- Detecting lateral movement in Azure AD
- Analysing Google Workspace logs for data leakage
- Tracking cross-cloud resource access attempts
- Detecting container breakout and pod escalation
- Monitoring Kubernetes audit logs for privilege abuse
- Investigating serverless function abuse
- Analysing cloud storage access patterns
- Tracking data egress from cloud environments
- Detecting persistence via Lambda triggers or Cloud Functions
- Using AI to prioritise cloud security findings
- Building detection logic for multi-cloud architectures
- Integrating CSPM data into threat hunting workflows
Module 9: Adversarial AI and Defender Countermeasures - Understanding how attackers use AI and ML
- Detecting AI-generated phishing content
- Identifying deepfake voice and video attacks
- Spotting automated credential stuffing with intelligent rotation
- Defending against model inversion and data extraction attacks
- Recognising adversarial examples that fool classifiers
- Monitoring for poisoning attacks on training data
- Detecting model stealing through query analysis
- Protecting internal ML systems from exploitation
- Implementing detection logic for GAN-generated malware
- Using defensive AI to detect AI-powered attacks
- Creating red team profiles for adversarial simulation
- Training models to recognise synthetic user behaviour
- Building watchdog systems for model integrity
- Establishing AI usage governance policies
Module 10: Incident Response Integration - Seamless handoff from hunting to incident response
- Automating evidence packaging for forensics
- Generating incident timelines from hunt findings
- Populating IR playbooks with enriched context
- Triggering containment actions based on confidence scores
- Integrating with ticketing systems like Jira and ServiceNow
- Using hunt results to update IR runbooks
- Creating executive summaries for breach communication
- Preserving chain of custody in digital evidence
- Analysing attacker dwell time and TTP coverage
- Conducting post-incident threat hunts for residual access
- Mapping attacker infrastructure for legal action
- Reporting mean time to detect and respond
- Improving response efficacy through feedback loops
- Demonstrating risk reduction to compliance teams
Module 11: Custom Tooling & Scripting for Scalability - Building reusable Python scripts for data collection
- Creating APIs to connect disjointed security tools
- Automating report generation with templated outputs
- Developing custom dashboards using Grafana and Kibana
- Designing CLI tools for internal SOC use
- Integrating with Slack and email for alert notification
- Scripting bulk IOC ingest and sweep operations
- Building lightweight detection validators
- Creating data visualisation tools for executive briefings
- Automating compliance checks using CIS benchmarks
- Developing audit trail analyzers for privilege changes
- Building file integrity monitors with hashing validation
- Scripting cross-platform forensic data collection
- Using Jupyter Notebooks for exploratory analysis
- Documenting and sharing tools across teams
Module 12: Advanced Threat Hunting Techniques - Hunting for fileless malware and memory-resident threats
- Detecting DNS tunneling and covert channels
- Analysing SSL/TLS certificate anomalies
- Investigating DGA-generated domain requests
- Tracking API key misuse and token abuse
- Identifying peer-to-peer command and control
- Analysing Windows registry persistence mechanisms
- Detecting WMI and PowerShell-based attacks
- Monitoring scheduled task creation and modification
- Investigating LSASS memory dumping attempts
- Analysing suspicious service installations
- Detecting rogue SSH key deployments
- Tracking unusual process injection techniques
- Identifying Golden Ticket and Silver Ticket usage
- Proactively hunting for zero-day indicators
Module 13: Metrics, Reporting & Stakeholder Communication - Measuring the ROI of threat hunting activities
- Calculating reduction in mean time to detect (MTTD)
- Tracking number of threats identified pre-breach
- Demonstrating risk reduction to executive leadership
- Creating visual reports for board-level review
- Translating technical findings into business impact
- Using KPIs to justify security budget increases
- Reporting on detection coverage across MITRE ATT&CK
- Tracking false positive reduction over time
- Measuring analyst efficiency gains
- Building executive dashboards with live data
- Presenting findings in non-technical language
- Structuring monthly threat landscape summaries
- Generating compliance-aligned risk reports
- Automating recurring compliance and audit reports
Module 14: Building Your AI-Driven Threat Hunting Program - Assessing organisational readiness for AI-powered hunting
- Securing executive sponsorship and budget approval
- Defining scope, team structure, and success criteria
- Integrating with existing SOC workflows
- Establishing regular hunting cadence and rotation
- Creating a knowledge base of past hunts and findings
- Developing internal training materials for team scaling
- Setting up feedback mechanisms for continuous improvement
- Conducting peer review of hunting hypotheses
- Implementing version control and documentation standards
- Planning for scalability across departments and regions
- Integrating with third-party MSSP or managed detection services
- Establishing metrics review meetings with leadership
- Creating a roadmap for AI model maturity advancement
- Designing a long-term skill development pathway
Module 15: Capstone Project & Certification - Selecting a high-impact threat scenario for your environment
- Developing a detailed hunting hypothesis with AI augmentation
- Collecting and preparing relevant telemetry data
- Executing a full threat hunt using learned methodologies
- Applying machine learning models to detect anomalies
- Generating a comprehensive technical report
- Creating an executive summary with business implications
- Proposing detection rule updates based on findings
- Recommending policy or configuration changes
- Presenting results using stakeholder-aligned messaging
- Submitting for expert review and feedback
- Revising and finalising the capstone package
- Documenting lessons learned and process improvements
- Earning your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn and professional profiles
- Understanding how attackers use AI and ML
- Detecting AI-generated phishing content
- Identifying deepfake voice and video attacks
- Spotting automated credential stuffing with intelligent rotation
- Defending against model inversion and data extraction attacks
- Recognising adversarial examples that fool classifiers
- Monitoring for poisoning attacks on training data
- Detecting model stealing through query analysis
- Protecting internal ML systems from exploitation
- Implementing detection logic for GAN-generated malware
- Using defensive AI to detect AI-powered attacks
- Creating red team profiles for adversarial simulation
- Training models to recognise synthetic user behaviour
- Building watchdog systems for model integrity
- Establishing AI usage governance policies
Module 10: Incident Response Integration - Seamless handoff from hunting to incident response
- Automating evidence packaging for forensics
- Generating incident timelines from hunt findings
- Populating IR playbooks with enriched context
- Triggering containment actions based on confidence scores
- Integrating with ticketing systems like Jira and ServiceNow
- Using hunt results to update IR runbooks
- Creating executive summaries for breach communication
- Preserving chain of custody in digital evidence
- Analysing attacker dwell time and TTP coverage
- Conducting post-incident threat hunts for residual access
- Mapping attacker infrastructure for legal action
- Reporting mean time to detect and respond
- Improving response efficacy through feedback loops
- Demonstrating risk reduction to compliance teams
Module 11: Custom Tooling & Scripting for Scalability - Building reusable Python scripts for data collection
- Creating APIs to connect disjointed security tools
- Automating report generation with templated outputs
- Developing custom dashboards using Grafana and Kibana
- Designing CLI tools for internal SOC use
- Integrating with Slack and email for alert notification
- Scripting bulk IOC ingest and sweep operations
- Building lightweight detection validators
- Creating data visualisation tools for executive briefings
- Automating compliance checks using CIS benchmarks
- Developing audit trail analyzers for privilege changes
- Building file integrity monitors with hashing validation
- Scripting cross-platform forensic data collection
- Using Jupyter Notebooks for exploratory analysis
- Documenting and sharing tools across teams
Module 12: Advanced Threat Hunting Techniques - Hunting for fileless malware and memory-resident threats
- Detecting DNS tunneling and covert channels
- Analysing SSL/TLS certificate anomalies
- Investigating DGA-generated domain requests
- Tracking API key misuse and token abuse
- Identifying peer-to-peer command and control
- Analysing Windows registry persistence mechanisms
- Detecting WMI and PowerShell-based attacks
- Monitoring scheduled task creation and modification
- Investigating LSASS memory dumping attempts
- Analysing suspicious service installations
- Detecting rogue SSH key deployments
- Tracking unusual process injection techniques
- Identifying Golden Ticket and Silver Ticket usage
- Proactively hunting for zero-day indicators
Module 13: Metrics, Reporting & Stakeholder Communication - Measuring the ROI of threat hunting activities
- Calculating reduction in mean time to detect (MTTD)
- Tracking number of threats identified pre-breach
- Demonstrating risk reduction to executive leadership
- Creating visual reports for board-level review
- Translating technical findings into business impact
- Using KPIs to justify security budget increases
- Reporting on detection coverage across MITRE ATT&CK
- Tracking false positive reduction over time
- Measuring analyst efficiency gains
- Building executive dashboards with live data
- Presenting findings in non-technical language
- Structuring monthly threat landscape summaries
- Generating compliance-aligned risk reports
- Automating recurring compliance and audit reports
Module 14: Building Your AI-Driven Threat Hunting Program - Assessing organisational readiness for AI-powered hunting
- Securing executive sponsorship and budget approval
- Defining scope, team structure, and success criteria
- Integrating with existing SOC workflows
- Establishing regular hunting cadence and rotation
- Creating a knowledge base of past hunts and findings
- Developing internal training materials for team scaling
- Setting up feedback mechanisms for continuous improvement
- Conducting peer review of hunting hypotheses
- Implementing version control and documentation standards
- Planning for scalability across departments and regions
- Integrating with third-party MSSP or managed detection services
- Establishing metrics review meetings with leadership
- Creating a roadmap for AI model maturity advancement
- Designing a long-term skill development pathway
Module 15: Capstone Project & Certification - Selecting a high-impact threat scenario for your environment
- Developing a detailed hunting hypothesis with AI augmentation
- Collecting and preparing relevant telemetry data
- Executing a full threat hunt using learned methodologies
- Applying machine learning models to detect anomalies
- Generating a comprehensive technical report
- Creating an executive summary with business implications
- Proposing detection rule updates based on findings
- Recommending policy or configuration changes
- Presenting results using stakeholder-aligned messaging
- Submitting for expert review and feedback
- Revising and finalising the capstone package
- Documenting lessons learned and process improvements
- Earning your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn and professional profiles
- Building reusable Python scripts for data collection
- Creating APIs to connect disjointed security tools
- Automating report generation with templated outputs
- Developing custom dashboards using Grafana and Kibana
- Designing CLI tools for internal SOC use
- Integrating with Slack and email for alert notification
- Scripting bulk IOC ingest and sweep operations
- Building lightweight detection validators
- Creating data visualisation tools for executive briefings
- Automating compliance checks using CIS benchmarks
- Developing audit trail analyzers for privilege changes
- Building file integrity monitors with hashing validation
- Scripting cross-platform forensic data collection
- Using Jupyter Notebooks for exploratory analysis
- Documenting and sharing tools across teams
Module 12: Advanced Threat Hunting Techniques - Hunting for fileless malware and memory-resident threats
- Detecting DNS tunneling and covert channels
- Analysing SSL/TLS certificate anomalies
- Investigating DGA-generated domain requests
- Tracking API key misuse and token abuse
- Identifying peer-to-peer command and control
- Analysing Windows registry persistence mechanisms
- Detecting WMI and PowerShell-based attacks
- Monitoring scheduled task creation and modification
- Investigating LSASS memory dumping attempts
- Analysing suspicious service installations
- Detecting rogue SSH key deployments
- Tracking unusual process injection techniques
- Identifying Golden Ticket and Silver Ticket usage
- Proactively hunting for zero-day indicators
Module 13: Metrics, Reporting & Stakeholder Communication - Measuring the ROI of threat hunting activities
- Calculating reduction in mean time to detect (MTTD)
- Tracking number of threats identified pre-breach
- Demonstrating risk reduction to executive leadership
- Creating visual reports for board-level review
- Translating technical findings into business impact
- Using KPIs to justify security budget increases
- Reporting on detection coverage across MITRE ATT&CK
- Tracking false positive reduction over time
- Measuring analyst efficiency gains
- Building executive dashboards with live data
- Presenting findings in non-technical language
- Structuring monthly threat landscape summaries
- Generating compliance-aligned risk reports
- Automating recurring compliance and audit reports
Module 14: Building Your AI-Driven Threat Hunting Program - Assessing organisational readiness for AI-powered hunting
- Securing executive sponsorship and budget approval
- Defining scope, team structure, and success criteria
- Integrating with existing SOC workflows
- Establishing regular hunting cadence and rotation
- Creating a knowledge base of past hunts and findings
- Developing internal training materials for team scaling
- Setting up feedback mechanisms for continuous improvement
- Conducting peer review of hunting hypotheses
- Implementing version control and documentation standards
- Planning for scalability across departments and regions
- Integrating with third-party MSSP or managed detection services
- Establishing metrics review meetings with leadership
- Creating a roadmap for AI model maturity advancement
- Designing a long-term skill development pathway
Module 15: Capstone Project & Certification - Selecting a high-impact threat scenario for your environment
- Developing a detailed hunting hypothesis with AI augmentation
- Collecting and preparing relevant telemetry data
- Executing a full threat hunt using learned methodologies
- Applying machine learning models to detect anomalies
- Generating a comprehensive technical report
- Creating an executive summary with business implications
- Proposing detection rule updates based on findings
- Recommending policy or configuration changes
- Presenting results using stakeholder-aligned messaging
- Submitting for expert review and feedback
- Revising and finalising the capstone package
- Documenting lessons learned and process improvements
- Earning your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn and professional profiles
- Measuring the ROI of threat hunting activities
- Calculating reduction in mean time to detect (MTTD)
- Tracking number of threats identified pre-breach
- Demonstrating risk reduction to executive leadership
- Creating visual reports for board-level review
- Translating technical findings into business impact
- Using KPIs to justify security budget increases
- Reporting on detection coverage across MITRE ATT&CK
- Tracking false positive reduction over time
- Measuring analyst efficiency gains
- Building executive dashboards with live data
- Presenting findings in non-technical language
- Structuring monthly threat landscape summaries
- Generating compliance-aligned risk reports
- Automating recurring compliance and audit reports
Module 14: Building Your AI-Driven Threat Hunting Program - Assessing organisational readiness for AI-powered hunting
- Securing executive sponsorship and budget approval
- Defining scope, team structure, and success criteria
- Integrating with existing SOC workflows
- Establishing regular hunting cadence and rotation
- Creating a knowledge base of past hunts and findings
- Developing internal training materials for team scaling
- Setting up feedback mechanisms for continuous improvement
- Conducting peer review of hunting hypotheses
- Implementing version control and documentation standards
- Planning for scalability across departments and regions
- Integrating with third-party MSSP or managed detection services
- Establishing metrics review meetings with leadership
- Creating a roadmap for AI model maturity advancement
- Designing a long-term skill development pathway
Module 15: Capstone Project & Certification - Selecting a high-impact threat scenario for your environment
- Developing a detailed hunting hypothesis with AI augmentation
- Collecting and preparing relevant telemetry data
- Executing a full threat hunt using learned methodologies
- Applying machine learning models to detect anomalies
- Generating a comprehensive technical report
- Creating an executive summary with business implications
- Proposing detection rule updates based on findings
- Recommending policy or configuration changes
- Presenting results using stakeholder-aligned messaging
- Submitting for expert review and feedback
- Revising and finalising the capstone package
- Documenting lessons learned and process improvements
- Earning your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn and professional profiles
- Selecting a high-impact threat scenario for your environment
- Developing a detailed hunting hypothesis with AI augmentation
- Collecting and preparing relevant telemetry data
- Executing a full threat hunt using learned methodologies
- Applying machine learning models to detect anomalies
- Generating a comprehensive technical report
- Creating an executive summary with business implications
- Proposing detection rule updates based on findings
- Recommending policy or configuration changes
- Presenting results using stakeholder-aligned messaging
- Submitting for expert review and feedback
- Revising and finalising the capstone package
- Documenting lessons learned and process improvements
- Earning your Certificate of Completion from The Art of Service
- Adding your credential to LinkedIn and professional profiles