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Vulnerability record · CVE-2026-22807 · published 21 January 2026

CVE-2026-22807: Vllm code injection vulnerability

Vllm · Vllm

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.

9.8 CVSS 3.1 Critical EPSS 0.83% · top 44.2% CWE-94 · Code injection
9.8CVSS 3.1 base score
0.83%EPSS exploitation probability, 30 days
NoNot in CISA KEV
1Affected product versions listed by NVD
17References
21 Jul 2026Last modified by NVD

Description

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.

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Affected products

1 vulnerable configurations from NVD's CPE data, grouped by vendor and product.

References

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Related vulnerabilities

Same products first, then exploited flaws of the same weakness class.

9.8CVE-2026-25960Vllm server-side request forgery (ssrf) vulnerabilityvLLM is an inference and serving engine for large language models (LLMs). The SSRF protection fix for CVE-2026-24779 add in 0.15.1 can be bypassed in…EPSS 0.72%9.8CVE-2026-22778Vllm sensitive information in log file vulnerabilityvLLM is an inference and serving engine for large language models (LLMs). From 0.8.3 to before 0.14.1, when an invalid image is sent to vLLM's multim…EPSS 3.8%9.8CVE-2025-47277Vllm deserialization of untrusted data vulnerabilityvLLM, an inference and serving engine for large language models (LLMs), has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments u…EPSS 0.96%9.8CVE-2025-32444Vllm deserialization of untrusted data vulnerabilityvLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.6.5 and prior to 0.8.5, having vLLM in…EPSS 1.8%9.8CVE-2024-11041Vllm deserialization of untrusted data vulnerabilityvllm-project vllm version v0.6.2 contains a vulnerability in the MessageQueue.dequeue() API function. The function uses pickle.loads to parse receive…EPSS 1.6%9.1CVE-2026-48746Vllm http request smuggling vulnerabilityvLLM is an inference and serving engine for large language models (LLMs). From 0.3.0 until 0.22.0, a vulnerability in ASGI web servers and starlette'…EPSS 1.2%9.0CVE-2025-29783Vllm deserialization of untrusted data vulnerabilityvLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. When vLLM is configured to use Mooncake, unsafe deserialization…EPSS 0.73%8.8CVE-2026-54232Vllm uncontrolled search path element vulnerabilityvLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.1, the vLLM Dockerfile is vulnerable to a dependency confusio…EPSS 0.56%

Source: NIST National Vulnerability Database (record CVE-2026-22807), CISA KEV, FIRST EPSS (scores of 2026-09-26). This page is refreshed as NVD updates the record.