A AegiFlow
MEDIUMCVSS 4.3EPSS 0.3%

CVE-2026-71486

CVE-2026-71486 updated by NVD

Published
2026-09-04
Modified
2026-09-11
EPSS percentile
27%
Sources
github-advisory, nvd

Summary

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.

Affected packages

EcosystemPackageAffected versionsFixed versions
PyPIvllm0.26.0

Remediation: Upgrade to 0.26.0 or later.

References

Includes data from the GitHub Advisory Database, licensed under CC-BY 4.0.

Includes data from the National Vulnerability Database (NIST). NVD data is in the public domain; this page is not endorsed by NIST.

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EPSS scores provided by the FIRST.org Exploit Prediction Scoring System.