{"id":"GHSA-q97c-p368-75c4","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 \u003c= 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\u003e1 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).","aliases":["CVE-2026-115916","PYSEC-2026-4347"],"modified":"2026-10-29T11:10:41.396326766Z","published":"2026-10-28T21:15:08Z","database_specific":{"github_reviewed_at":"2026-10-28T21:15:08Z","nvd_published_at":"2026-10-26T18:17:39Z","cwe_ids":["CWE-129","CWE-193"],"severity":"MODERATE","github_reviewed":true},"references":[{"type":"WEB","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":"WEB","url":"https://github.com/vllm-project/vllm/pull/59491"},{"type":"WEB","url":"https://github.com/vllm-project/vllm/commit/37cecc8141e2dcba9dd534897a164d4baaf27229"},{"type":"PACKAGE","url":"https://github.com/vllm-project/vllm"},{"type":"WEB","url":"https://github.com/vllm-project/vllm/releases/tag/v0.32.0"}],"affected":[{"package":{"name":"vllm","ecosystem":"PyPI","purl":"pkg:pypi/vllm"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"0.32.0"}]}],"versions":["0.0.1","0.1.0","0.1.1","0.1.2","0.1.3","0.1.4","0.1.5","0.1.6","0.1.7","0.10.0","0.10.1","0.10.1.1","0.10.2","0.11.0","0.11.1","0.11.2","0.12.0","0.13.0","0.14.0","0.14.1","0.15.0","0.15.1","0.16.0","0.17.0","0.17.1","0.18.0","0.18.1","0.19.0","0.19.1","0.2.0","0.2.1","0.2.1.post1","0.2.2","0.2.3","0.2.4","0.2.5","0.2.6","0.2.7","0.20.0","0.20.1","0.20.2","0.21.0","0.22.0","0.22.1","0.23.0","0.24.0","0.25.0","0.25.1","0.26.0","0.27.0","0.27.1","0.28.0","0.29.0","0.3.0","0.3.1","0.3.2","0.3.3","0.30.0","0.31.0","0.4.0","0.4.0.post1","0.4.1","0.4.2","0.4.3","0.5.0","0.5.0.post1","0.5.1","0.5.2","0.5.3","0.5.3.post1","0.5.4","0.5.5","0.6.0","0.6.1","0.6.1.post1","0.6.1.post2","0.6.2","0.6.3","0.6.3.post1","0.6.4","0.6.4.post1","0.6.5","0.6.6","0.6.6.post1","0.7.0","0.7.1","0.7.2","0.7.3","0.8.0","0.8.1","0.8.2","0.8.3","0.8.4","0.8.5","0.8.5.post1","0.9.0","0.9.0.1","0.9.1","0.9.2"],"database_specific":{"source":"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2026/10/GHSA-q97c-p368-75c4/GHSA-q97c-p368-75c4.json"}}],"schema_version":"1.9.2","severity":[{"type":"CVSS_V3","score":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H"}]}