Why Traditional Validation Is Not Enough
In traditional software, input validation means checking types, lengths, and formats. Is this a valid email? Is this number within range? AI input validation is fundamentally harder because the input is natural language — there is no schema, no type system, and no clear boundary between valid and malicious text.
A SQL injection attack uses specific syntax (' OR 1=1 --). A prompt injection uses persuasive English: "Please ignore your previous instructions." You cannot filter that with a regex without also blocking legitimate questions about AI instructions.
Three Validation Strategies
Regex patterns for known injection signatures. Fast and cheap. Catches obvious attacks but misses creative variations. Use as the first filter, not the only one.
A lightweight ML model trained to classify inputs as benign or adversarial. Catches variations and novel attacks that patterns miss. More expensive but much more robust.
Structural techniques that separate user input from system instructions. Delimiters, input framing, and sandboxing user content within the prompt architecture.