vllm vulnerability

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 2026Updated 2 Oct 202666 sources
CVSS 4.3 ✓ VERIFIED REFERENCE

What happened

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 versions

vllm: < 0.26.0 Fixed: See vendor advisory.

Why it matters

Review the vendor advisory and exposure of the affected product to determine operational impact.

Detection & mitigation

  • Apply vendor-provided updates or mitigations.
  • Review affected product exposure and access logs.

Public PoC references

RepositoryAuthorFirst seenReference
github.comNVD reference2026-08-17Verified