NVIDIA AI Red Team · June 27, 2024

Secure LLM Tokenizers to Maintain Application Integrity

Why it matters

NVIDIA demonstrates a model supply-chain attack in which a privileged adversary edits a tokenizer JSON file so visible words map to different token IDs. The change can make the model interpret "deny" as "allow" or corrupt decoded output while leaving the model weights untouched.

My takeaway: Version, sign, inventory, and verify tokenizers together with model weights and code. Check artifact integrity again at runtime, protect remote repositories and local caches, and log token IDs or tokenizer versions alongside input and output strings so an encoding or decoding mismatch remains visible during investigation.
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