CVE-2026-71486

MediumCVSS 4.3/10Last modified Oct 23, 2026

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.

Metrics

CVSS 3.1 4.3/10CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L

Weakness enumeration

CWE-400 CWE-770

Affected software

Vendor	Product	Versions
vllm-project	vllm	< 0.26.0

References

https://github.com/vllm-project/vllm/commit/8e61b646e2d157f9b93451fa048f9c8530c8a67bPatch
https://github.com/vllm-project/vllm/pull/47260Issue Tracking, Patch
https://github.com/vllm-project/vllm/releases/tag/v0.26.0Release Notes
https://github.com/vllm-project/vllm/security/advisories/GHSA-8737-qx52-hjffExploit, Vendor Advisory, Mitigation

Timeline

Published: Aug 17, 2026
Last modified: Oct 23, 2026
NVD status: Analyzed

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