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Advanced Threat Detection and Response Engineering

$199.00
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A tailored course, built for your situation

Advanced Threat Detection and Response Engineering

A next-step implementation course for cyber intrusion analysts advancing in technical leadership

$199 one-time
24-hour access provisioning 30-day money-back guarantee Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Moving from reactive analysis to engineered defense is challenging without a structured path.

The situation this course is for

Cyber intrusion analysts often hit a ceiling when transitioning from incident response to building prevention systems. The shift requires mastery of detection logic, telemetry optimization, and automation, not just forensic analysis. Without a clear implementation framework, professionals risk plateauing in roles while demand surges for engineers who can design resilient detection architectures.

Who this is for

A mid-career cyber intrusion analyst with strong incident response experience, now aiming to lead in detection engineering, SOC automation, or threat-informed defense design.

Who this is not for

Entry-level analysts needing foundational certification prep or professionals focused only on compliance reporting without technical implementation.

What you walk away with

  • Design detection rules that reduce false positives by aligning with attacker behavior patterns
  • Implement automated containment workflows using SOAR integrations
  • Map telemetry gaps to MITRE ATT&CK and prioritize sensor deployment
  • Build adversary emulation plans that validate detection coverage
  • Lead cross-functional coordination between IR, engineering, and identity teams

The 12 modules (with all 144 chapters)

Module 1. Foundations of Detection Engineering
Establish principles of high-signal detection design and lifecycle management.
12 chapters in this module
  1. From alerts to detections: redefining the objective
  2. The detection engineering mindset
  3. Core components of a detection rule
  4. Balancing sensitivity and specificity
  5. Detection taxonomy and classification
  6. Version control for detection logic
  7. Common failure modes in detection design
  8. Integrating threat intelligence into rules
  9. Using logs effectively: beyond volume
  10. Detection coverage modeling
  11. Metrics that matter: precision, recall, dwell time
  12. Building a detection review process
Module 2. Telemetry Strategy and Sensor Placement
Optimize data collection for maximum detection efficacy with minimal overhead.
12 chapters in this module
  1. Principles of effective telemetry
  2. Endpoint vs network vs cloud visibility
  3. Identifying high-value data sources
  4. Log normalization and enrichment
  5. Cost-benefit analysis of data ingestion
  6. Designing for EDR telemetry consumption
  7. Cloud-native logging strategies
  8. API-based data collection patterns
  9. User and entity behavior analytics (UEBA) inputs
  10. Threat-driven sensor placement
  11. Data retention and legal considerations
  12. Telemetry gap assessment framework
Module 3. MITRE ATT&CK for Detection Design
Use ATT&CK as an engineering blueprint, not just a reference model.
12 chapters in this module
  1. Beyond mapping: engineering from ATT&CK
  2. Tactics as detection categories
  3. Technique-specific detection patterns
  4. Sub-technique granularity and value
  5. Mapping detection rules to ATT&CK
  6. Using ATT&CK to identify blind spots
  7. Customizing ATT&CK for internal use
  8. Integrating ATT&CK with threat intel
  9. Adversary emulation planning with ATT&CK
  10. Measuring ATT&CK coverage realistically
  11. Automating ATT&CK alignment
  12. Contributing to ATT&CK community
Module 4. Detection Rule Development
Write, test, and deploy rules in Sigma, YARA, SPL, and custom query languages.
12 chapters in this module
  1. Sigma syntax and best practices
  2. Writing YARA rules for malware detection
  3. SPL for Splunk-based detections
  4. KQL for Microsoft Defender and Sentinel
  5. Testing detection logic in staging
  6. Rule performance optimization
  7. Avoiding resource exhaustion
  8. Cross-platform rule design
  9. Rule documentation standards
  10. Automated validation of rules
  11. Handling encrypted traffic in rules
  12. Versioning and rollback strategies
Module 5. Automated Response Workflows
Design SOAR playbooks that accelerate containment without over-automating.
12 chapters in this module
  1. SOAR architecture fundamentals
  2. Use cases for automated containment
  3. Playbook design patterns
  4. Risk assessment for automation
  5. Integrating EDR with orchestration tools
  6. Automated evidence collection
  7. User notification workflows
  8. Cloud instance isolation automation
  9. Email quarantine automation
  10. False positive handling in playbooks
  11. Approval workflows and human-in-the-loop
  12. Monitoring playbook effectiveness
Module 6. Threat Hunting Methodology
Shift from reactive to proactive discovery using hypothesis-driven models.
12 chapters in this module
  1. Hunting vs detection: key differences
  2. Developing testable hypotheses
  3. Hypothesis generation from intel
  4. Data requirements for hunting
  5. Using ATT&CK for hunting scoping
  6. Timeline analysis techniques
  7. Anomaly detection methods
  8. Behavioral clustering for hunting
  9. Hunting in cloud environments
  10. Documenting and sharing findings
  11. Measuring hunting program success
  12. Integrating hunting into operations
Module 7. Adversary Emulation Planning
Run controlled red team operations to validate detection coverage.
12 chapters in this module
  1. Emulation vs penetration testing
  2. Building realistic attack scenarios
  3. Scoping emulation exercises
  4. Selecting techniques to emulate
  5. Safe execution in production
  6. Coordinating with operations teams
  7. Logging and monitoring during emulation
  8. Measuring detection efficacy
  9. Post-exercise reporting
  10. Integrating findings into roadmap
  11. Automating emulation validation
  12. Building a repeatable emulation cycle
Module 8. Cloud Intrusion Analysis
Detect and respond to threats in AWS, Azure, and GCP with platform-specific logic.
12 chapters in this module
  1. Cloud attack surface fundamentals
  2. Identity-centric threats in cloud
  3. Detecting misconfigurations at scale
  4. Analyzing IAM policy changes
  5. CloudTrail, Azure Activity, GCP Audit logs
  6. Serverless threat detection
  7. Container and Kubernetes threats
  8. Detecting cloud cryptojacking
  9. Data exfiltration patterns in cloud
  10. Cloud-to-on-prem lateral movement
  11. Multi-cloud detection strategies
  12. Cloud workload protection platforms
Module 9. Identity-Centric Threat Detection
Focus on credential abuse, privilege escalation, and identity federation risks.
12 chapters in this module
  1. Why identity is the new perimeter
  2. Detecting pass-the-hash attacks
  3. Golden ticket detection methods
  4. Abnormal login pattern analysis
  5. Detection of Azure AD attacks
  6. Monitoring privileged access sessions
  7. Detecting service account abuse
  8. Federation token theft indicators
  9. Identity provider logging gaps
  10. Integrating PAM with detection systems
  11. Behavioral baselines for user accounts
  12. Detecting insider threat precursors
Module 10. Detection Validation and Metrics
Measure what matters: coverage, speed, accuracy, and operational impact.
12 chapters in this module
  1. Defining success metrics for detection
  2. Mean time to detect (MTTD) measurement
  3. False positive rate tracking
  4. Detection coverage scoring models
  5. Using purple team assessments
  6. Benchmarking against industry standards
  7. Reporting to technical leadership
  8. Board-level security metrics
  9. Operational burden of detections
  10. Cost of detection ownership
  11. Continuous improvement cycles
  12. Feedback loops from incident response
Module 11. Cross-Team Collaboration Models
Lead integration between SOC, engineering, IT, and identity teams.
12 chapters in this module
  1. SOC as a service provider model
  2. Integrating detection with DevSecOps
  3. Collaborating with network engineering
  4. Working with identity and access teams
  5. Engaging with cloud platform teams
  6. Threat intelligence sharing protocols
  7. Incident coordination frameworks
  8. Building detection requirements with developers
  9. Feedback mechanisms for rule tuning
  10. Security champion networks
  11. Documenting cross-team dependencies
  12. Managing priorities across functions
Module 12. Leading Detection Program Maturity
Evolve from ad hoc alerts to a strategic, scalable detection engineering function.
12 chapters in this module
  1. Assessing current program maturity
  2. Roadmap for detection engineering
  3. Resource planning and staffing
  4. Tooling selection and integration
  5. Developing internal training
  6. Creating documentation standards
  7. Building executive support
  8. Aligning with enterprise risk
  9. Scaling detection across regions
  10. Innovation in detection methods
  11. Succession planning for leads
  12. Continuous adaptation framework

How this maps to your situation

  • Analyst transitioning to engineering role
  • SOC lead designing detection standards
  • Threat hunter seeking structured methodology
  • Security architect integrating detection into platform design

Before vs. after

Before
Relies on vendor alerts and manual analysis, struggles to scale detection logic, lacks framework for measuring coverage or impact.
After
Designs and implements high-fidelity detection systems, measures program efficacy, and leads cross-functional security engineering initiatives.

What's included with your purchase

  • 12 modules with 12 chapters each (144 chapters)
  • Downloadable templates and worked examples for every module
  • Hand-built implementation playbook delivered alongside course access
  • 30-day money-back guarantee

Delivery and format

  • Course and learning environment access provisioned within 24 hours of purchase
  • Hand-built implementation playbook delivered alongside course access

Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.

Time investment: Approximately 60-70 hours of focused learning, designed for completion over 8-10 weeks with flexible pacing.

If nothing changes
Without structured advancement into detection engineering, professionals risk remaining in reactive roles while organizations increasingly reward those who can build scalable, automated defenses.

How this compares to the alternatives

Unlike certification prep courses or vendor-specific training, this program focuses on implementation-grade design patterns, cross-platform logic, and leadership in detection engineering, skills not covered in CISSP, CEH, or platform-specific curricula.

Frequently asked

Is this course focused on a specific tool or platform?
No. The course teaches implementation principles and design patterns applicable across platforms, with examples in Sigma, KQL, SPL, and cloud-native logging systems.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Who is the ideal participant?
Cyber intrusion analysts moving into detection engineering, threat hunting leadership, or SOC automation roles.
$199 one-time. Approximately 60-70 hours of focused learning, designed for completion over 8-10 weeks with flexible pacing..

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

30-day money-back guarantee· 144 chapters· Hand-built playbook included· Account access within 24 hours
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