Visão Geral
Este curso aborda os aspectos de segurança relacionados às arquiteturas Retrieval-Augmented Generation (RAG), explorando riscos, ameaças, vulnerabilidades e controles necessários para proteger aplicações corporativas baseadas em IA Generativa. O participante aprenderá a identificar e mitigar ataques direcionados a pipelines de recuperação, bancos vetoriais, bases de conhecimento, documentos corporativos e integrações com Large Language Models (LLMs). O curso apresenta práticas modernas de segurança, governança, monitoramento e conformidade para implementação segura de soluções RAG em ambientes empresariais.
Conteúdo Programatico
Module 1: Introduction to RAG Security
- Evolution of AI security challenges
- Security fundamentals for RAG systems
- Enterprise threat landscape
- Attack surfaces in RAG architectures
- Security principles and objectives
- Overview of AI security frameworks
Module 2: RAG Architecture Risk Analysis
- Components of RAG architectures
- Trust boundaries identification
- Data flow security analysis
- Threat modeling methodologies
- Risk assessment techniques
- Security-by-design principles
Module 3: Prompt Injection Attacks Against RAG
- Prompt injection fundamentals
- Direct injection attacks
- Indirect injection attacks
- Document-based prompt manipulation
- Detection techniques
- Defensive strategies
Module 4: Context Poisoning and Knowledge Manipulation
- Context poisoning concepts
- Malicious document insertion
- Knowledge base tampering
- Retrieval manipulation attacks
- Integrity validation controls
- Prevention and mitigation approaches
Module 5: Vector Database Security
- Security considerations for vector databases
- Access control mechanisms
- Embedding protection strategies
- Data isolation techniques
- Secure indexing practices
- Monitoring vector storage environments
Module 6: Knowledge Base Security
- Enterprise knowledge protection
- Document classification methodologies
- Data leakage prevention
- Sensitive information controls
- Content governance practices
- Secure knowledge lifecycle management
Module 7: Retrieval Layer Security
- Secure retrieval architectures
- Query validation mechanisms
- Access-aware retrieval
- Authorization enforcement
- Retrieval monitoring techniques
- Retrieval integrity validation
Module 8: Privacy and Compliance
- Data privacy requirements
- Regulatory compliance frameworks
- Personal data protection
- Data retention policies
- Auditability requirements
- Compliance monitoring processes
Module 9: Security Monitoring and Threat Detection
- Security observability fundamentals
- Threat detection strategies
- Security logging and telemetry
- Anomaly detection techniques
- Incident response integration
- Continuous security monitoring
Module 10: Governance and Risk Management
- AI governance frameworks
- Risk management methodologies
- Security policy development
- Third-party risk management
- Audit and compliance programs
- Responsible AI principles
Module 11: Secure Enterprise RAG Architectures
- Zero Trust principles for RAG
- Identity and access management integration
- Secure multi-tenant architectures
- Defense-in-depth strategies
- Enterprise deployment patterns
- Operational security best practices
Module 12: RAG Security Workshop
- Threat modeling exercises
- Prompt injection testing laboratories
- Context poisoning simulations
- Security validation assessments
- Monitoring and governance implementation
- Final enterprise RAG security project