A tailored course, built for your situation
Mastering OWASP for AI Robotics Executives
A tailored course for senior AI leaders shaping intelligent systems with defensible design foundations.
$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.
Peer challenges to security-by-design decisions in AI-driven robotics systems lack grounding in shared frameworks.
The situation this course is for
Even with strong internal alignment, AI robotics leaders face frequent pushback on security architecture from engineering, product, and compliance teams. Without accessible, source-backed reasoning, justifications risk being dismissed as opinion rather than standard.
Who this is for
Senior AI executives in robotics and intelligent systems companies who are responsible for translating security frameworks into operational design choices.
Who this is not for
Junior developers, compliance auditors, or non-technical risk officers who don't directly shape AI system architecture.
What you walk away with
- Articulate OWASP principles with specific implementation examples from AI robotics contexts
- Reference tested control patterns when debating architecture tradeoffs
- Respond confidently to peer challenges using cited sources and precedent
- Map OWASP recommendations to internal robotics safety and resilience workflows
- Build a personal repository of defensible design justifications
The 12 modules (with all 144 chapters)
Module 1. Foundations of OWASP in AI Systems
Establish the relevance of OWASP to intelligent robotics platforms, focusing on real-world risk scenarios and how OWASP's structure applies.
12 chapters in this module
- Origins of OWASP in modern AI
- Core principles for AI attack surfaces
- Mapping AI functions to OWASP categories
- Why OWASP applies to robotics decision logic
- Case: LLM-driven navigation exploits
- Common misinterpretations to avoid
- How OWASP complements ISO 27001
- Integrating threat modeling early
- Security vs. safety in AI robotics
- Framework adoption patterns in R&D
- Key differences from web app context
- Defining scope for robotics teams
Module 2. OWASP Top 10 for Robotics AI
Deep-dive into each of the OWASP Top 10 items as they manifest in robotics systems, with AI-specific attack vectors.
12 chapters in this module
- AI injection in sensor interpretation
- Misleading model feedback loops
- Data poisoning in training pipelines
- Model inversion in edge devices
- Sensitive data leakage from logs
- Overreliance on unverified outputs
- Inadequate monitoring in autonomy
- Improper access controls on AI APIs
- Supply chain risks in pre-trained models
- Model denial-of-service scenarios
- Security gaps in reinforcement learning
- Real-world breach patterns in robots
Module 3. Source-Backed Reasoning Patterns
Learn how to cite and apply OWASP documentation, NIST crosswalks, and real-world audits to defend architectural choices.
12 chapters in this module
- Citing OWASP ASVS correctly
- Linking to NIST AI Risk Framework
- Using MITRE ATLAS for context
- When to reference DORA
- Building citation trails
- How to structure a defense memo
- Internal stakeholder objections
- Engineering team counterpoints
- Product roadmap tradeoffs
- Precedent from past robotics audits
- Using public breach reports
- Creating defensible playbooks
Module 4. Defensible Design in Practice
Apply OWASP guidelines to actual robotics design decisions using templates and annotated examples.
12 chapters in this module
- Mapping autonomy stack to OWASP
- Designing for model rollback
- Logging AI decisions securely
- Validating sensor inputs
- Securing OTA update paths
- Enforcing least privilege in AI
- Mitigating prompt injection risks
- Testing for adversarial inputs
- Calibrating safety thresholds
- Documenting design rationale
- Versioning control logic
- Peer review checklist design
Module 5. Cross-Functional Alignment
Foster collaboration between security, engineering, and compliance teams using shared OWASP-based language.
12 chapters in this module
- Translating OWASP for engineers
- Creating team-specific summaries
- Workshop facilitation guide
- Aligning roadmap priorities
- Managing technical debt debates
- Involving legal teams early
- Compliance officer communication
- Vendor audit preparation
- Third-party model risk
- Contractual security clauses
- Internal audit coordination
- Escalation paths for disagreements
Module 6. Threat Modeling with OWASP
Use OWASP's framework to conduct structured threat modeling sessions for robotics AI components.
12 chapters in this module
- Introducing STRIDE to AI
- Asset identification in robotics
- Threat tree for navigation models
- Data flow mapping with OWASP
- Identifying trust boundaries
- Model integrity threats
- Runtime integrity checks
- Adversarial environment simulation
- Red teaming AI decision logic
- Automated threat detection
- Generating mitigation tickets
- Prioritizing based on blast radius
Module 7. Implementation Playbook Development
Build a repeatable playbook for applying OWASP principles across robotics development cycles.
12 chapters in this module
- Creating standard operating procedures
- Integrating with CI/CD pipelines
- Template for AI control review
- Checklist for new AI modules
- Automated security gates
- Review frequency scheduling
- Ownership assignment framework
- Incident response integration
- Updating playbooks quarterly
- Onboarding new engineers
- Measuring compliance adoption
- Linking to product KPIs
Module 8. Audit and Compliance Integration
Align OWASP implementation with internal and external audit requirements.
12 chapters in this module
- SOC 2 control mapping
- ISO 27001 crosswalk
- Preparing for security audits
- Documenting control evidence
- Handling auditor questions
- Generating SoA content
- Tracking control exceptions
- Remediation tracking system
- Audit trail for AI decisions
- Versioning security controls
- Reporting to leadership
- Continuous monitoring design
Module 9. AI Supply Chain Security
Apply OWASP to third-party models, pre-trained weights, and open-source dependencies in robotics AI.
12 chapters in this module
- Vendor model risk assessment
- Evaluating open-source AI tools
- License compliance checks
- Backdoor detection strategies
- Model provenance tracking
- SBOM for AI components
- Dependency vulnerability scans
- Contractual security terms
- Penetration testing vendors
- Monitoring for model drift
- Revocation procedures
- Fallback design patterns
Module 10. Real-World Case Applications
Analyze actual robotics and AI system breaches using OWASP as a diagnostic lens.
12 chapters in this module
- Case: Autonomous delivery robot hack
- Root cause using OWASP
- Missed control opportunities
- Recommended mitigations
- Case: Drone swarm manipulation
- OWASP mapping exercise
- Post-mortem documentation
- Public regulator response
- Lessons for internal teams
- Applying insights to new builds
- Updating training curricula
- Sharing learnings across units
Module 11. Executive Communication Strategy
Translate technical OWASP decisions into clear, defensible narratives for leadership and board-level audiences.
12 chapters in this module
- Distilling risk for executives
- Creating executive summaries
- Visualizing attack surfaces
- Reporting on AI resilience
- Balancing innovation and risk
- Framing investment needs
- Measuring security maturity
- Avoiding fear-based language
- Highlighting competitive edge
- Linking to business outcomes
- Preparing Q&A for leadership
- Owning the narrative
Module 12. Sustaining Defensible AI Leadership
Establish long-term practices to ensure OWASP integration evolves with AI robotics innovation.
12 chapters in this module
- Building a center of excellence
- Mentoring next-gen leaders
- Knowledge retention plan
- Cross-org collaboration model
- Staying current with OWASP updates
- Contributing to OWASP
- Publishing internal best practices
- Benchmarking against peers
- Tracking emerging threats
- Annual review cycle
- Succession planning
- Closing the feedback loop
How this maps to your situation
- When initiating new robotics AI projects
- During internal security audits
- Ahead of vendor assessments
- Before product launches with AI components
Before vs. after
Before
Security discussions devolve into opinion-based debates without shared reference points.
After
Every design choice is anchored in OWASP, with citations and examples ready for peer review.
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 3 hours per module, designed for completion over 6-8 weeks with flexible pacing.
If nothing changes
Without a defensible framework, security decisions risk being overruled, leading to increased exposure in AI-driven robotics systems.
How this compares to the alternatives
Unlike generic cybersecurity courses, this program is tailored to AI robotics leaders and focuses on OWASP application with concrete, defensible examples relevant to intelligent systems.
Frequently asked
Is this course technical or strategic?
It bridges both, providing technical depth in OWASP while focusing on strategic communication and defensibility for leadership contexts.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I share this with my team?
Each enrollment is individual, but the implementation playbook is designed for team rollout.
$199 one-time. Approximately 3 hours per module, designed for completion over 6-8 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