{"id":"CVE-2026-115916","aliases":["GHSA-q97c-p368-75c4"],"url":"https://o3.security/vulnerability/CVE-2026-115916","summary":"vLLM: Out-of-vocabulary prompt token id passes input validation and triggers a CUDA device-side assert (engine crash / DoS)","details":"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.\n\n## Root cause\n`vllm/v1/engine/input_processor.py` accepts a token id when `id <= max(tokenizer.max_token_id, model_config.get_vocab_size() - 1)`.\n`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.\nThe engine bound therefore becomes `max(32000, 31999) = 32000`, and id 32000 is accepted.\nThe 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.\n\n## Affected\n- 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.\n- 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).\n\n## Suggested fix \nmax_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](https://github.com/vllm-project/vllm/pull/59491), released in v0.32.0.\n\n## Reporter\nShijie Lyu (GitHub shijie-lyu lshjhf@gmail.com). Reported privately per SECURITY.\n\nThis advisory was fixed in [MR59491](https://github.com/vllm-project/vllm/pull/59491).","published":"2026-10-26T17:18:17.582Z","modified":"2026-10-28T02:59:28.887380594Z","cvss":{"score":6.5,"severity":"MEDIUM","vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H"},"epss":null,"cisaKev":null,"exploitsKnown":null,"affectedPackages":[{"ecosystem":"PyPI","name":"vllm","fixedVersion":"0.32.0"}],"fix":{"url":"https://github.com/vllm-project/vllm/commit/37cecc8141e2dcba9dd534897a164d4baaf27229","label":"vllm-project/vllm@37cecc8"},"references":[{"type":"WEB","url":"https://github.com/vllm-project/vllm/releases/tag/v0.32.0"},{"type":"ADVISORY","url":"https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/115xxx/CVE-2026-115916.json"},{"type":"ADVISORY","url":"https://github.com/vllm-project/vllm/security/advisories/GHSA-q97c-p368-75c4"},{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-115916"},{"type":"FIX","url":"https://github.com/vllm-project/vllm/commit/37cecc8141e2dcba9dd534897a164d4baaf27229"},{"type":"FIX","url":"https://github.com/vllm-project/vllm/pull/59491"},{"type":"PACKAGE","url":"https://github.com/vllm-project/vllm"}],"provenance":{"sources":["OSV.dev","FIRST.org (EPSS)"],"lastVerified":"2026-10-28T02:59:28.887380594Z"}}