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
