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MEDIUM Received

CVE-2026-71486

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.

Published 17 Aug 2026, 20:16 UTC Last modified 17 Aug 2026, 20:16 UTC
01

Attack profile

The conditions required to exploit this vulnerability and its potential impact.

Attack vector Network
Attack complexity Low
Privileges required Low
User interaction None
Scope Unchanged
Confidentiality None
Integrity None
Availability Low
Exploitability2.8
Impact1.4
02

Affected products

Product applicability statements supplied with the NVD record.

NVD has not published structured affected-product data for this record.
03

Weakness classification

CWE categories help security teams group the underlying software weakness.

04

Source references

External advisories, patches and technical reports attached to this CVE record.