Hệ Thống Bảo Vệ AI & An Ninh Mạng - Thực Hành Kiểm Thử Xâm Nhập với AI Agent

77% of enterprises faced Generative AI breaches last year (IBM 2025). This hands-on course teaches you to deploy production guardrails against prompt injection, hallucinations, and cyber attacks using Llama Guard 3, AWS Bedrock, and CrewAI. Master open-source frameworks like GuardrailsAI, Nemo Guardrails, and Haystack to secure real AI applications.

What You'll Learn:

1. GUARDRAIL FRAMEWORKS

• Nemo Guardrails: Production-grade dialog management & intent filtering

• GuardrailsAI: RAIL specs, validator policies, output structuring

• AWS Bedrock Guardrails: Enterprise content policy configuration

• Haystack Evaluators: RAG faithfulness/SAS metrics

• Llama Guard 3: Multimodal (vision+text) jailbreak detection

2. SECURITY TESTING TOOLS

• Garak: Red Teaming to scan LLM vulnerability (encoding/XFilteration/profanity)

• CrewAI + OWASP ZAP: Scan Web Vulnerabilities with AI-powered web penetration testing

• Prompt-Guard: Real-time injection attack blocking

3. PLATFORMS & MODELS

• AWS Bedrock: Cloud-based guardrail deployment

• Hugging Face: Access to phi3/prompt-guard models

• Phi-3.5-vision-instruct: Multimodal safety enforcement

• phi3-hallucination-judge: Hallucination scoring engine

• FastRAG: Secure retrieval-augmented generation pipelines

Below is the course details

1. Input Security Guardrails

• Nemo Guardrails: Dialog management for intent-based filtering

• Llama Guard 3: Vision-text hybrid moderation (NSFW/jailbreak detection)

• Prompt-Guard: Real-time injection blocking

2. Output Validation Systems

• phi3-hallucination-judge: Quantify truthfulness scores

• GuardrailsAI Validators: Enforce PII/deny-topic policies

• LLM-as-Judge Fallbacks: Context relevancy checks

3. Vulnerability Scanning

• Garak Probes:

  • Encoding attacks

  • XFilteration exploits

  • Profanity detection

4. AI-Powered Cybersecurity

• CrewAI Penetration testing:

  • Web vulnerability scanning

  • ZAP Proxy automation

  • Multi-agent threat hunting

5. Enterprise Platform Guardrails

• AWS Bedrock:

  • Content policy configuration

  • Multimodal image guardrails

• Nemo Production Deployment:

  • Intent classification workflows

  • Custom validator integration

6. RAG Security & Evaluation

• Haystack Framework:

  • Pipeline construction

  • SAS/faithfulness metrics

• GuardrailsAI RAIL Specs:

  • Output structure validation

  • On-fail remediation policies

7. Multimodal Agentic Safety

• ReAct Architecture: Multi-hop reasoning

• Phi-3.5-vision-instruct:

  • Nutritional analysis case study

  • Compliance checks

KEY HANDS-ON PROJECTS

1. • Nemo Intent Firewall: Block restricted queries in production chatbots

   • GuardrailsAI HIPAA Enforcer: PII redaction & deny-topic policies

   • CrewAI Web Vulnerability Scanner: Automated XSS/SQLi detection

   • Multimodal Jailbreak Detector: NSFW/image attack prevention

   • RAG Audit Dashboard: SAS scoring for retrieval faithfulness

Who Should Enroll:

This course is ideal for AI developers, data scientists, business leaders, and enthusiasts eager to enhance their understanding of ethical AI practices quickly. Whether you aim to apply ethical considerations to current projects or seek to broaden your knowledge of AI safety measures, this course will equip you with the insights needed for responsible AI development.

Join Us:

Embrace the opportunity to shape the future of AI by embedding ethical considerations and safety measures into the fabric of AI technologies. Enroll in "AI Guardrails: Ensuring Ethical and Safe AI Deployments" and take a significant step towards responsible and safe AI deployment.