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# Protecting Your RAG Agent

**[Viget](https://daily.dev/sources/viget)** · 12 min read · 1 upvotes · 0 comments

## Summary

A practical walkthrough of techniques used to protect a RAG agent from malicious users and prompt injection attacks. Covers rate limiting with FastAPI, request validation with Pydantic (including control character rejection and length limits), token usage caps via Amazon Bedrock settings, regex-based prompt filtering for common jailbreak patterns, AWS Bedrock Guardrails for content and PII filtering, and wrapping user input in XML tags paired with system prompt instructions to mark untrusted data. Code examples are provided for each technique using Python, FastAPI, Pydantic AI, and Amazon Bedrock.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.viget.com/articles/protecting-your-rag-agent>

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- [How to Build Production-Grade AI Guardrails for Enterprise Applications: A Practical Guide](https://daily.dev/posts/how-to-build-production-grade-ai-guardrails-for-enterprise-applications-a-practical-guide-zengcqngi) · freeCodeCamp · 1 upvotes · 0 comments

---

Tags: [#rag](https://daily.dev/tags/rag), [#fastapi](https://daily.dev/tags/fastapi), [#prompt-injection](https://daily.dev/tags/prompt-injection), [#amazon-bedrock](https://daily.dev/tags/amazon-bedrock)

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