| Component | vLLM |
| Severity | medium (CVSS 4.3) |
| CVSS vector | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L |
| Published (NVD) | 2026-08-17 |
| Last modified | 2026-10-02 |
| Affected versions | vllm < 0.26.0 |
| Fixed in | 0.26.0 |
| Weakness | CWE-400CWE-770 |
| CISA KEV | not listed |
NVD description
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the /v1/completions/derender and /v1/chat/completions/derender endpoints accept caller-supplied GenerateResponse objects whose generate_responses, choices, token_ids, prompt_logprobs, logprobs.content, top_logprobs, and routed_experts structures are processed by OnlineDerenderer and tokenizer.decode before max_model_len, max_tokens, max_num_seqs, or response-size limits are enforced, allowing an authenticated API client to consume excessive CPU and memory and produce oversized responses. This issue is fixed in version 0.26.0.
What to do
- Upgrade vLLM to
0.26.0or later. - Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
- NVD: CVE-2026-71486
- https://github.com/vllm-project/vllm/security/advisories/GHSA-8737-qx52-hjff
- https://github.com/vllm-project/vllm/commit/8e61b646e2d157f9b93451fa048f9c8530c8a67b
- https://github.com/vllm-project/vllm/pull/47260
- https://github.com/vllm-project/vllm/releases/tag/v0.26.0
Read more
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