Gemini 3 Secure AI Training in Bangkok, Thailand

The Gemini 3 Secure AI Training is a specialized program focused on helping organizations deploy and use Gemini 3 securely, with strong emphasis on security, privacy, governance, and risk management for Generative AI systems.

The course teaches how to design secure-by-design AI architectures, implement guardrails, and ensure compliance and auditability when using Gemini 3 in enterprise environments.

Security Risks in Generative AI & Gemini 3

• Threat landscape for Generative AI
• Differences between chatbot and application security
• Gemini 3-specific risk considerations
• Regulatory and compliance context

Secure Gemini 3 Architecture

• Reference secure architectures
• Network and API security patterns
• Environment separation (dev/test/prod)
• Defense-in-depth for AI systems

Identity, Access & Least Privilege

• IAM for Gemini 3 access
• Role-based access control
• Service accounts and key management
• Separation of duties

Prompt & Context Security

• Protecting system and developer prompts
• Preventing prompt leakage
• Context isolation strategies
• Secure prompt storage and versioning

Prompt Injection & Manipulation Defense

• Understanding prompt injection attacks
• Input validation and sanitization
• Output filtering and constraints
• Defense strategies

Data Security & Privacy

• Handling sensitive and regulated data
• Data minimization and redaction
• Encryption in transit and at rest
• Data residency and compliance

Guardrails & Policy Enforcement

• Content filters and moderation
• Business rule enforcement
• Policy-as-code concepts
• Automated compliance checks

Logging, Monitoring & Auditability

• Logging prompts and responses safely
• Traceability of AI decisions
• Audit trails for compliance
• Security monitoring and alerting

Secure Integration with Enterprise Systems

• API gateway and proxy patterns
• Securing downstream tool calls
• Network segmentation
• Monitoring external integrations

Human-in-the-Loop Security Controls

• Approval workflows for high-risk actions
• Supervisor review steps
• Manual overrides
• Escalation handling

Testing & Red Teaming Gemini 3 Systems

• Security testing for AI apps
• Adversarial testing
• Simulating misuse scenarios
• Continuous security validation

Incident Response for AI Systems

• Detecting AI-related incidents
• Containment and rollback
• Root cause analysis
• Post-incident improvements

Compliance & Governance Frameworks

• Mapping to ISO, NIST, SOC2, GDPR (conceptual)
• Internal AI governance models
• Documentation and evidence collection
• Regulatory readiness

Secure Deployment & Operations

• CI/CD security for AI apps
• Secrets rotation and key management
• Configuration drift detection
• Ongoing security posture management

Best Practices & Secure AI Playbooks

• Secure-by-design checklists
• Operational playbooks
• Change management
• Continuous improvement

Hands-on Exercises

Summary and Conclusion