intermediate~2h
LLM Safety Guardrails (Engineering)
Engineering-level safety measures for production LLM apps — prompt injection defense, content filtering, and output validation
4
Subtopics
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Exercises
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Projects
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Quiz Qs
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Flashcards
▶📚 Prerequisites(2)
🎓 Learning objectives
- •Define prompt injection and describe how it works in agent systems
- •Implement input and output guardrail layers
- •Know what Llama Guard and NeMo Guardrails do
- •Prevent system prompt leakage
- •Design a defense-in-depth safety architecture
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📂 Subtopics
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Prompt Injection Attacks: Direct vs. Indirect, and Why They're Hard to Prevent
Jailbreaking and Misuse: Common Techniques and Why Alignment Alone Isn't Enough
Output Guardrails: Content Filtering, Toxicity Detection, and PII Redaction
Defense Strategies: Layered Validation, NeMo Guardrails, and Constitutional AI
Related concepts
agent-patternsllm-foundationsmcp-protocol