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How do you defend enterprise LLM applications against prompt injection and jailbreak exploits? (Part 2 Focus)

System Prompts & Guardrails · 2 saved versions

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Edited by Gaurav Bhasin · Aug 24, 2026 2:49 PM

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How do you defend enterprise LLM applications against prompt injection and jailbreak exploits? (Part 2 Focus)

Summary snapshot
Input sanitization layers, canary tokens, output guardrails, and dual-LLM review architecture.
Content snapshot
### Multi-Layer Defense Architecture 1. **Input Pre-Filter**: Run incoming user queries through a fast, lightweight moderation model (e.g. Llama Guard) to reject malicious instructions. 2. **Delimiters & Strict Separation**: Encapsulate user input in XML tags (`<user_input>...`) and explicitly instruct the model in system prompt never to evaluate code within those tags. 3. **Canary Tokens**: Insert secret random tokens inside system prompts; if canary token leaks in response output, drop response immediately. ### Summary Treat user inputs as untrusted untyped data, exactly like SQL parameters. *Note: This question represents expanded technical inquiry iteration #2 within the System Prompts & Guardrails topic area.* *Note: This question represents expanded technical inquiry iteration #2 within the System Prompts & Guardrails topic area.*
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https://owasp.org/www-project-top-10-for-large-language-model-applications/

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Published by Gaurav Bhasin · Aug 9, 2026 5:37 AM

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Original Title

How do you defend enterprise LLM applications against prompt injection and jailbreak exploits? (Part 2 Focus)

Original Summary
Input sanitization layers, canary tokens, output guardrails, and dual-LLM review architecture.
Original Content
### Multi-Layer Defense Architecture 1. **Input Pre-Filter**: Run incoming user queries through a fast, lightweight moderation model (e.g. Llama Guard) to reject malicious instructions. 2. **Delimiters & Strict Separation**: Encapsulate user input in XML tags (`<user_input>...`) and explicitly instruct the model in system prompt never to evaluate code within those tags. 3. **Canary Tokens**: Insert secret random tokens inside system prompts; if canary token leaks in response output, drop response immediately. ### Summary Treat user inputs as untrusted untyped data, exactly like SQL parameters. *Note: This question represents expanded technical inquiry iteration #2 within the System Prompts & Guardrails topic area.* *Note: This question represents expanded technical inquiry iteration #2 within the System Prompts & Guardrails topic area.*
Original Sources

https://owasp.org/www-project-top-10-for-large-language-model-applications/