Medium [CVE-2026-71486] Denial of Service via unbounded token ID decoding
This medium-severity Red Hat Linux advisory covers CVE-2026-71486 affecting Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI).
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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. A flaw was found in vLLM.
These endpoints process the objects without enforcing output bounds or response-size limits. This can lead to excessive consumption of CPU and memory resources, resulting in a Denial of Service (DoS).
Red Hat severity: Moderate — CVSS 4.3 (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L). Weakness: CWE-770.
Affected Red Hat products: Red Hat AI Inference Server; Red Hat Enterprise Linux AI (RHEL AI) 3; Red Hat OpenShift AI (RHOAI). Red Hat does not currently list a fixing RHSA for this CVE.
- < 0.26.0
Official advisory · high-confidence parse· fetched 49 minutes ago·verify at source
- 0.26.0
Official advisory · high-confidence parse· fetched 49 minutes ago·verify at source
Mitigation
Upgrade to a fixed release: 0.26.0. That is the remediation for this advisory.
The vendor advisory may list additional interim mitigations or workarounds not captured here — review it before change work.
Official advisory · high-confidence parse· fetched 49 minutes ago·verify at source
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