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Fencer Intel
medium 4.3

CVE-2026-71486 json

vLLM: Derender endpoints decode caller-supplied GenerateResponse token IDs without output bounds

published 2mo ago modified 19d ago also EUVD-2026-60376 , GHSA-8737-qx52-hjff , PYSEC-2026-3936

cvss
4.3
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.4%
EPSS 0.4% chance of exploitation in 30 days, percentile 31%
public exploits
0
none known

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.

Patch / fix

  • pypi vllm 0.26.0
  • vllm-project vllm 0.26.0
  • vllm vllm 0.26.0

Is CVE-2026-71486 in your dependencies? Fencer shows which of your repositories are affected as soon as an advisory lands, and opens the fix as a pull request.

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Vendor advisories

What the vendors themselves say about their products: affected, fixed or not affected, and what to do.

red hat product security vex CVE-2026-71486 updated cvss 4.3

vllm: vLLM: Denial of Service via unbounded token ID decoding

  • Red Hat AI Inference Server rhaii/vllm-tpu-rhel9, rhaiis/vllm-cpu-rhel9, rhaiis/vllm-tpu-rhel9, rhaiis/vllm-cuda-rhel9, rhaiis/vllm-rocm-rhel9, rhaii/vllm-neuron-rhel9, +2 more Red Hat Enterprise Linux AI (RHEL AI) 3 rhelai3/bootc-gaudi-rhel9 Red Hat OpenShift AI (RHOAI) rhoai/odh-vllm-gaudi-rhel9, rhoai/odh-kserve-agent-rhel9, rhoai/odh-kserve-router-rhel9, rhoai/odh-llm-d-kv-cache-rhel9, rhoai/odh-kserve-controller-rhel9, rhoai/odh-th-torch-cuda-py312-rhel9, +1 more
    affected: workaround, no fix available “Fix deferred”
  • Red Hat AI Inference Server 3.5 rhaii/vllm-cpu-rhel9 1791473614, rhaii/vllm-cuda-rhel9 1791473631, rhaii/vllm-rocm-rhel9 1791425869, rhaii/vllm-gaudi-rhel9 1791427182, rhaii/vllm-spyre-rhel9 1791818357
    fixed: vendor fix RHSA-2026:82415
  • Red Hat Enterprise Linux AI 3.5 rhelai3/bootc-cuda-rhel9 1793135861, rhelai3/bootc-rocm-rhel9 1793135863, rhelai3/bootc-aws-cuda-rhel9 1793194817, rhelai3/bootc-gcp-cuda-rhel9 1793194815, rhelai3/disk-image-cuda-rhel9 1793206758, rhelai3/bootc-azure-cuda-rhel9 1793194815, +1 more
    fixed: vendor fix RHSA-2026:92452

Red Hat CSAF VEX © Red Hat, Inc., from https://security.access.redhat.com/data/csaf/v2/vex/; changed: reduced to product statuses and remediations. CC BY 4.0 · csaf

CISA SSVC

Exploitation
none
Automatable
no
Technical impact
partial
Assessed
2mo ago

Exploit prediction

0.37% chance of exploitation in the next 30 days, higher than 31% of all scored CVEs (FIRST EPSS, 2026-11-11).

Exploits and checks

  • github.com https://github.com/vllm-project/vllm/security/advisories/GHSA-8737-qx52-hjff referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 4.3 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
GitHub 3.1 4.3 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
OSV 3.1 4.3 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L

Affected packages

ecosystem package affected fixed in
pypi vllm
<0.26.0
0.26.0

Affected products

  • vllm-project vllm

Classification

Weakness
  • CWE-400 Uncontrolled Resource Consumption
  • CWE-770 Allocation of Resources Without Limits or Throttling

References

Sources

Fencer Intel keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.

CPEs and fixed versions use Anchore's correction of NVD's data: Added CPE configurations because not yet analyzed by NVD.