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Fencer Vulns
high 8.8

CVE-2026-22807 json

vLLM affected by RCE via auto_map dynamic module loading during model initialization

published 2026-01-21 9 mo ago modified 2026-09-10 1 mo ago also EUVD-2026-3678 , GHSA-2pc9-4j83-qjmr , PYSEC-2026-2010

cvss
8.8
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
1.0%
EPSS 1.0% chance of exploitation in 30 days, percentile 62%
public exploits
0
none known

Summary

vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.14.0, vLLM loads Hugging Face `auto_map` dynamic modules during model resolution without gating on `trust_remote_code`, allowing attacker-controlled Python code in a model repo/path to execute at server startup. An attacker who can influence the model repo/path (local directory or remote Hugging Face repo) can achieve arbitrary code execution on the vLLM host during model load. This happens before any request handling and does not require API access. Version 0.14.0 fixes the issue.

Patch / fix

  • pypi vllm 0.14.0
  • Red Hat Red Hat AI Inference Server 3.2 1772160593, 1772160625
  • Red Hat Red Hat AI Inference Server 3.3 1782352847, 1782352919, 1782353093
  • Red Hat Red Hat OpenShift AI 2.25 1772093278, 1776259063, 1783998774, 1783998857
  • Red Hat Red Hat OpenShift AI 3.3 1770956034
  • Red Hat Red Hat OpenShift AI 3.4 1772204861

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-2026-22807 updated cvss 8.8

vLLM: vLLM: Arbitrary code execution via untrusted model loading

  • Red Hat AI Inference Server rhaiis/vllm-tpu-rhel9
    affected: workaround, no fix available
  • Red Hat Enterprise Linux AI (RHEL AI) 3 rhelai3/bootc-cuda-rhel9, rhelai3/bootc-aws-cuda-rhel9, rhelai3/bootc-gcp-cuda-rhel9, rhelai3/bootc-azure-cuda-rhel9
    affected: workaround, no fix planned “Will not fix”
  • Red Hat AI Inference Server 3.2 rhaiis 1772160593, rhaiis 1772160625
    fixed: vendor fix RHSA-2026:3461
  • Red Hat AI Inference Server 3.3 rhaiis/vllm-cuda-rhel9 1782352847, rhaiis/vllm-rocm-rhel9 1782353093, rhaiis/vllm-spyre-rhel9 1782352919
    fixed: vendor fix RHSA-2026:30089
  • Red Hat OpenShift AI 2.25 rhoai 1772093278, rhoai 1776259063, rhoai/odh-vllm-cuda-rhel9 1783998774, rhoai/odh-vllm-rocm-rhel9 1783998857
    fixed: vendor fix RHSA-2026:10184
  • Red Hat OpenShift AI 3.3 rhoai 1770956034
    fixed: vendor fix RHSA-2026:3713
  • Red Hat OpenShift AI 3.4 rhoai 1772204861
    fixed: vendor fix RHSA-2026:5119
  • Red Hat OpenShift AI (RHOAI) rhoai/odh-kserve-agent-rhel9, rhoai/odh-kserve-router-rhel9, rhoai/odh-kserve-controller-rhel9, rhoai/odh-kserve-storage-initializer-rhel9
    not affected: vulnerable code not in execute path
show 1 more
  • Red Hat OpenShift AI 2.25 rhoai 1772093237, rhoai 1772093250, rhoai 1772093252, rhoai 1772093260, rhoai 1772093266, rhoai 1772093272, +213 more Red Hat OpenShift AI 3.3 rhoai 1769162595, rhoai 1769436305, rhoai 1769519975, rhoai 1770277795, rhoai 1770735854, rhoai 1770754585, +71 more Red Hat OpenShift AI 3.4 rhoai 1772204847, rhoai 1772204866, rhoai 1772204867, rhoai 1772204879, rhoai 1772204882, rhoai 1772204883, +74 more
    not affected: vulnerable code not present

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
total
Assessed
9 mo ago

Exploit prediction

0.98% chance of exploitation in the next 30 days, higher than 62% of all scored CVEs (FIRST EPSS, 2026-11-08).

CVSS scores

assigned by version score vector
CNA 3.1 8.8 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
CISA ADP 3.1 8.8 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
GitHub 3.1 8.8 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
NVD 3.1 9.8 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
OSV 3.1 8.8 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Affected packages

ecosystem package affected fixed in
pypi vllm
>=0.10.1, <0.14.0
0.14.0

Affected products

  • vllm-project vllm
  • Red Hat Red Hat AI Inference Server 3.2
  • Red Hat Red Hat AI Inference Server 3.3
  • Red Hat Red Hat OpenShift AI 2.25
  • Red Hat Red Hat OpenShift AI 3.3
  • Red Hat Red Hat OpenShift AI 3.4
  • Red Hat Red Hat AI Inference Server
  • Red Hat Red Hat Enterprise Linux AI (RHEL AI) 3
  • Red Hat Red Hat OpenShift AI (RHOAI)

Classification

Weakness
  • CWE-94 Improper Control of Generation of Code

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.

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