CVE Catalog

CVE-2026-71486

MediumCVSS 4.3
Published: Updated: Translated: NVD NIST

Exploitation Probability (EPSS)

Low risk
0.34%

27th percentile - higher than 27% of all known CVEs

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.

Risk Assessment

An authenticated API client can overload the server, causing excessive resource consumption and potential denial of service.

Recommendation

Update vLLM to version 0.26.0 or later to prevent excessive resource consumption.

Original NVD description (English source)

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.

Vulnerability data from NVD (NIST) · CISA KEV · EPSS