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Fencer Vulns
medium 4.3

CVE-2026-71486 json

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

published 2026-08-17 2 mo ago modified 2026-10-23 16 d ago also GHSA-8737-qx52-hjff , PYSEC-2026-3936 , EUVD-2026-60376

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 vllm 0.26.0

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
2 mo ago

Exploit prediction

0.37% chance of exploitation in the next 30 days, higher than 31% of all scored CVEs (FIRST EPSS, 2026-11-08).

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 Vulns 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.