CVE-2026-71486
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.
AI Insight
LLM-synthesized narrative grounded in this CVE's description and references.
Affected packages
Versions sourced from the GitHub Security Advisory.
| Package | Affected versions | Patched versions |
|---|---|---|
vllmPyPI | < 0.26.0 | 0.26.0 |
Affected products
1Patches
Vulnerability mechanics
References
6- github.com/advisories/GHSA-8737-qx52-hjffghsaADVISORY
- nvd.nist.gov/vuln/detail/CVE-2026-71486ghsaADVISORY
- github.com/vllm-project/vllm/commit/8e61b646e2d157f9b93451fa048f9c8530c8a67bnvdWEB
- github.com/vllm-project/vllm/pull/47260nvdWEB
- github.com/vllm-project/vllm/releases/tag/v0.26.0nvdWEB
- github.com/vllm-project/vllm/security/advisories/GHSA-8737-qx52-hjffnvdWEB
News mentions
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