CVE-2026-71486

medium

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.

References

https://github.com/vllm-project/vllm/security/advisories/GHSA-8737-qx52-hjff

https://github.com/vllm-project/vllm/releases/tag/v0.26.0

https://github.com/vllm-project/vllm/pull/47260

https://github.com/vllm-project/vllm/commit/8e61b646e2d157f9b93451fa048f9c8530c8a67b

Details

Source: Mitre, NVD

Published: 2026-08-17

Updated: 2026-08-18

Risk Information

CVSS v2

Base Score: 4

Vector: CVSS2#AV:N/AC:L/Au:S/C:N/I:N/A:P

Severity: Medium

CVSS v3

Base Score: 4.3

Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L

Severity: Medium

EPSS

EPSS: 0.00341