LLM Prompt Injection & Guardrail Security

Short summary

LLMs have no boundary between instructions and data, making them vulnerable to prompt injection through multiple vectors. Six defense layers (string filtering → human review) each have specific weaknesses; stacking raises the bar but isn't airtight. ASCII smuggling via hidden Unicode characters bypasses text-level review; the fix is raw-byte sanitization and deterministic checks at the application boundary.

• •Prompt injection exploits the lack of instruction/data boundary in LLM context windows
• •Six-layer defense progression demonstrates each layer's specific weaknesses and why layering alone is insufficient
• •ASCII smuggling using hidden Unicode characters bypasses human review; real-world fix is Unicode normalization and deterministic checks before tokenization

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