GHSA-q97c-p368-75c4MediumCVSS 6.5

vLLM: Out-of-vocabulary prompt token id passes input validation and triggers a CUDA device-side assert (engine crash / DoS)

Published
October 28, 2026
Last Modified
October 28, 2026

🔗 CVE IDs covered (1)

📋 Description

For a model whose vocabulary size is an exact multiple of the embedding padding size (64) — e.g. any Llama-2-family model, vocab 32000 — a single request carrying a pre-tokenized prompt with token id equal to the vocab size (32000) passes vLLM's input-id validation but is one past the last embedding row. At tensor-parallel size 1 the embedding lookup does not mask indices, so the id reaches F.embedding out of range and raises a CUDA device-side assert, which poisons the engine's CUDA context and takes the engine down. Any client that can send pre-tokenized input (/v1/completions with prompt as token ids, /tokenize-fed flows, or the kv_transfer_params["prompt_token_ids"] reuse path) can trigger it.

Root cause

vllm/v1/engine/input_processor.py accepts a token id when id <= max(tokenizer.max_token_id, model_config.get_vocab_size() - 1). vllm/tokenizers/hf.py computes max_token_id = max(max(vocab.values()), tokenizer.vocab_size). For Llama-2 tokenizers max(vocab.values()) = 31999 but tokenizer.vocab_size = 32000, so max_token_id = 32000 — one greater than the largest valid id. The engine bound therefore becomes max(32000, 31999) = 32000, and id 32000 is accepted. The model's embedding has pad_vocab_size(32000, 64) = 32000 rows (no padding), valid indices 0..31999. At VocabParallelEmbedding.forward with tp_size == 1 there is no masking, so index 32000 hits F.embedding out of range.

Affected

  • tp=1 (single GPU per model — common per-copy layout). tp>1 masks via get_masked_input_and_mask, so the id is clamped, not an OOB — likely wrong output rather than a crash.
  • Models whose vocab is a multiple of 64 with tokenizer.vocab_size one past the max real id (Llama-2 family, vocab 32000, is the clear case). Qwen2.5 is NOT affected (padded headroom).

Suggested fix

max_token_id in vllm/tokenizers/hf.py now uses tokenizer.vocab_size - 1, so an id equal to the vocabulary size fails input validation instead of reaching the embedding. Fixed in MR59491, released in v0.32.0.

Reporter

Shijie Lyu (GitHub shijie-lyu lshjhf@gmail.com). Reported privately per SECURITY.

This advisory was fixed in MR59491.

🎯 Affected products1

  • pip/vllm:< 0.32.0

🔗 References (6)