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GEN5138 Mastering OWASP for Senior Health and AI Executives

$199.00
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A tailored course, built for your situation

Mastering OWASP for Senior Health and AI Executives

Turn security leadership into strategic advantage

$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.
Security reviews slowing down AI pilots in healthcare?

The situation this course is for

Many health AI leaders face delayed approvals, fragmented controls, and last-minute findings because security isn’t embedded early. That causes missed windows, eroded trust, and cost overruns.

Who this is for

Senior technical executive in healthcare AI, responsible for innovation velocity and compliance integrity

Who this is not for

Junior developers, standalone security analysts, or non-healthcare AI practitioners

What you walk away with

  • Faster alignment between AI development teams and security reviewers
  • Increased approval speed for pilot deployments with clear OWASP mapping
  • Higher-confidence decision-making on third-party components and APIs
  • Stronger influence when negotiating scope with engineering and compliance partners
  • Clearer audit trail that satisfies regulators without slowing innovation

The 12 modules (with all 144 chapters)

Module 1. Mapping OWASP Top 10 to healthcare AI attack surfaces
Define high-risk entry points in clinical AI systems by aligning OWASP categories with real-world patient data flows. Learn how to isolate authentication risks, API vulnerabilities, and model inference exploits unique to health settings. This foundation ensures your team prioritizes what matters.
12 chapters in this module
  1. Identifying injection risks in FHIR-based data pipelines
  2. Assessing authentication flaws in clinician-facing AI dashboards
  3. Model access controls and OWASP API Security Top 10 overlap
  4. How medical device integrations expand the attack surface
  5. Real-world breaches in health AI tied to broken object level access
  6. Prioritizing risks by clinical impact not just technical severity
  7. Securing AI inference endpoints against adversarial inputs
  8. Managing secrets in containerized health AI deployments
  9. Evaluating third-party libraries for known CVEs in medical AI
  10. Session management pitfalls in multi-tenant health platforms
  11. Logging and monitoring for OWASP-mapped incidents in real time
  12. Building risk heatmaps aligned to OWASP categories
Module 2. Embedding security decisions in AI product roadmaps
Shift from reactive security checks to proactive integration in development cycles. This module teaches how to insert OWASP-aligned gates at sprint planning, model freeze, and deployment phases without slowing momentum. You’ll learn to speak fluently across product, engineering, and compliance.
12 chapters in this module
  1. Aligning OWASP milestones with sprint planning meetings
  2. Creating lightweight threat models for AI feature teams
  3. Security criteria for AI vendor shortlists
  4. Integrating dependency scanning into CI/CD for AI projects
  5. Defining acceptable risk thresholds for pilot environments
  6. Working with data scientists on secure model packaging
  7. Documentation standards that pass internal review first time
  8. Fast-path approvals for low-risk AI components
  9. How to escalate OWASP findings without killing momentum
  10. Negotiating scope reductions that preserve security
  11. Tracking technical debt using OWASP severity ratings
  12. Building trust with engineering leads through shared outcomes
Module 3. Speaking fluently across compliance, engineering, and clinical teams
Gain recognition as the leader who bridges silos. This module focuses on translating OWASP concepts into language that resonates with regulators, engineers, and clinicians. You’ll develop negotiation frameworks and communication tools that reduce friction and increase trust.
12 chapters in this module
  1. Translating OWASP findings into clinical risk statements
  2. Presenting security trade-offs to non-technical sponsors
  3. How to explain SSRF risks to hospital IT procurement
  4. Speaking dev language: security debt vs. feature velocity
  5. Building credibility with security engineers through precision
  6. Aligning OWASP controls with HIPAA compliance requirements
  7. Creating executive summaries that compress technical depth
  8. Handling pushback from teams under delivery pressure
  9. Using real breach data to justify OWASP prioritization
  10. Documenting decisions for future auditor review
  11. Facilitating cross-functional workshops on AI risk
  12. Maintaining authority without blocking innovation
Module 4. Designing secure AI deployment patterns
Learn how to structure AI deployments that pass internal review quickly by baking in OWASP principles from day one. This includes container hardening, API gateways, model access policies, and monitoring configurations tailored to healthcare environments.
12 chapters in this module
  1. Hardening Docker images for clinical AI workloads
  2. Securing model serving endpoints using OWASP ASVS
  3. Network segmentation for AI inference clusters
  4. Zero-trust access to AI dashboards in hybrid clouds
  5. How to validate inputs against OWASP Input Validation Rules
  6. Protecting model weights from unauthorized access
  7. Rate limiting and abuse prevention for AI APIs
  8. Encryption strategies for AI training data at rest
  9. Secure logging of model predictions and inputs
  10. Session token security in patient-facing AI apps
  11. Managing API keys across dev, test, and prod
  12. Audit trail completeness for regulatory readiness
Module 5. Fast-tracking regulator confidence in AI pilots
Regulators move quickly when documentation is clear, consistent, and grounded in standards. This module shows how to structure evidence packages using OWASP mappings so that questions get answered before they’re asked.
12 chapters in this module
  1. Building evidence binders aligned to OWASP controls
  2. Preempting common FDA AI/ML post-market questions
  3. Documenting threat modeling outcomes for auditors
  4. How to map OWASP findings to NIST AI Risk Framework
  5. Preparing responses to simulated inspection requests
  6. Demonstrating continuous improvement in security posture
  7. Using automated scans to prove control effectiveness
  8. Versioning security documentation with model releases
  9. Creating runbooks for incident response in AI systems
  10. Showing mitigation progress on prior findings
  11. Linking OWASP remediation to patient safety claims
  12. Anticipating follow-up questions based on OWASP class
Module 6. Vendor selection with built-in OWASP alignment
Make smarter vendor choices by embedding OWASP requirements early. This module provides scoring frameworks, RFP language, and integration checklists so you can avoid costly rework and anchor partnerships on strong security foundations.
12 chapters in this module
  1. Evaluating AI vendors on OWASP Top 10 compliance
  2. Scoring third-party risk using OWASP ASVS levels
  3. Including OWASP language in vendor SLAs and contracts
  4. Running security due diligence interviews with vendors
  5. Assessing MLOps platforms for secure model management
  6. Validating penetration test results from vendor claims
  7. How to request and interpret SOC 2 reports for AI tools
  8. Building exit ramps when vendors fail OWASP benchmarks
  9. Integrating vendor components into internal OWASP tracking
  10. Enforcing container security standards pre-deployment
  11. Managing patch cycles for third-party AI libraries
  12. Creating joint remediation plans with vendor teams
Module 7. Reducing rework through early security validation
Avoid late-stage findings that delay launches. This module teaches how to implement lightweight validation steps early, threat modeling, design reviews, and prototype testing, that eliminate the most common OWASP-related rework.
12 chapters in this module
  1. Running threat modeling workshops before coding begins
  2. Using DFDs to expose OWASP risks in AI architectures
  3. Security criteria for AI model acceptance testing
  4. Validating input sanitization in early prototypes
  5. How to catch broken access control in staging
  6. Automating OWASP ZAP scans in development branches
  7. Reviewing third-party dependencies before integration
  8. Securing model training pipelines against poisoning
  9. Testing for insecure deserialization in AI services
  10. Validating error handling exposes no system details
  11. Checking for hardcoded secrets in submitted code
  12. Running lightweight audits before production freeze
Module 8. Building trust with engineering leads through shared outcomes
Security wins when it enables, not blocks. This module shows how to create shared KPIs, joint deliverables, and collaborative workflows that position security as an enabler of faster, cleaner AI delivery.
12 chapters in this module
  1. Co-defining success metrics with AI development teams
  2. Creating shared dashboards for security debt tracking
  3. Joint ownership of OWASP remediation timelines
  4. Celebrating secure launches as team achievements
  5. How to run blameless incident post-mortems
  6. Integrating security into agile ceremonies
  7. Providing actionable feedback not just policy citations
  8. Recognizing engineers who fix OWASP issues early
  9. Balancing speed and safety in high-pressure sprints
  10. Designing security spikes that accelerate delivery
  11. Using pair programming to spread security knowledge
  12. Measuring trust through voluntary compliance rates
Module 9. Creating repeatable security playbooks for AI innovation
Turn one-off wins into scalable processes. This module guides you through building living documents, implementation checklists, approval templates, and escalation paths, that survive leadership changes and compound value across projects.
12 chapters in this module
  1. Documenting approval workflows for new AI pilots
  2. Building OWASP-aligned security onboarding for new hires
  3. Creating boilerplate language for audit responses
  4. Templating threat modeling sessions for reuse
  5. Standardizing model card content with security sections
  6. How to version security playbooks across teams
  7. Automating playbook updates from scan results
  8. Linking playbook steps to Jira or ServiceNow tasks
  9. Training junior staff using internal playbook examples
  10. Updating controls based on new OWASP revisions
  11. Archiving outdated playbook versions securely
  12. Measuring playbook adoption across the org
Module 10. Scaling secure AI practices across business units
Go beyond your team to influence wider change. This module teaches how to replicate success across product lines, geographies, and divisions using lightweight governance, peer champions, and measurable benchmarks.
12 chapters in this module
  1. Identifying high-leverage teams for security adoption
  2. Training peer reviewers in other business units
  3. Setting up cross-unit OWASP alignment councils
  4. Sharing playbooks with regional compliance leads
  5. Adapting central policies to local clinical needs
  6. Measuring secure AI adoption across divisions
  7. Running centralized security bootcamps
  8. Creating internal certification paths for engineers
  9. Linking security maturity to promotion criteria
  10. Benchmarking against industry leaders in health AI
  11. Using data to show reduction in post-launch findings
  12. Scaling best practices without creating bottlenecks
Module 11. Staying ahead of OWASP revisions and emerging threats
Security isn’t static. This module prepares you to track updates to OWASP guidance, assess relevance to health AI, and lead proactive adjustments before incidents occur.
12 chapters in this module
  1. Subscribing to OWASP mailing lists and changelogs
  2. Evaluating new OWASP categories for healthcare relevance
  3. Tracking AI-specific threats in OWASP projects
  4. Assessing impact of new CWEs on existing AI systems
  5. Running tabletop exercises for new attack vectors
  6. Updating training materials after OWASP updates
  7. Communicating changes to stakeholders early
  8. Prioritizing patching based on exploit availability
  9. Monitoring dark web chatter for new AI exploits
  10. Engaging with OWASP communities for early insights
  11. Contributing health AI use cases to OWASP research
  12. Planning annual review cycles for security frameworks
Module 12. Leading with quiet confidence in high-stakes environments
Exceptional leaders don’t shout, they deliver. This final module integrates everything into a personal leadership model: how to project calm authority, earn trust without visibility stunts, and enable teams to move faster because you’re in charge.
12 chapters in this module
  1. Speaking with precision during crisis response
  2. Delegating OWASP tasks with clear ownership
  3. Maintaining focus on patient outcomes under pressure
  4. Balancing public statements with technical truth
  5. Building a reputation for reliability not drama
  6. Owning mistakes without losing authority
  7. Setting tone through documentation quality
  8. Hiring and promoting for security mindset
  9. Mentoring future leaders in secure AI
  10. Knowing when to escalate and when to absorb
  11. Creating space for innovation through strong foundations
  12. Leaving a legacy of compounding security excellence

How this maps to your situation

  • Health AI product delivery
  • Clinical system integration
  • Regulatory readiness
  • Cross-functional leadership

Before vs. after

Before
Security reviews slow down AI innovation, create tension between teams, and lead to late-stage surprises.
After
AI projects move faster with embedded OWASP alignment, regulators trust the evidence, and teams come to you first for guidance.

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: 90 minutes per week over three months, self-paced with immediate access.

If nothing changes
Without structured OWASP integration, health AI initiatives risk delayed launches, regulatory scrutiny, and erosion of cross-functional trust, especially as scrutiny increases.

How this compares to the alternatives

Unlike generic OWASP training, this course is tailored to health AI executives, focusing on influence, credibility, and project velocity, not just technical checklists.

Frequently asked

Is this course technical or strategic?
It’s both. Designed for senior leaders, it bridges deep OWASP understanding with real-world influence in healthcare AI delivery.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I share this with my team?
Each purchase grants access to one individual. Team licenses are available upon request.
$199 one-time. 90 minutes per week over three months, self-paced with immediate access..

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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