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HIGH · 7.5

CVE-2026-41523

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, an assert-based security check in vLLM's activation function loading allows any unauthenticated attacker to a...

Vulnerability Description

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, an assert-based security check in vLLM's activation function loading allows any unauthenticated attacker to achieve arbitrary code execution on the server by publishing a malicious HuggingFace model, when vLLM runs in Python optimized mode (python -O or PYTHONOPTIMIZE=1). This vulnerability is fixed in 0.22.0.

CVSS Score

7.5

HIGH

CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
REQUIRED
Scope
UNCHANGED
Confidentiality
HIGH
Integrity
HIGH
Availability
HIGH

Affected Products

VendorProductVersions
VllmVllm< 0.22.0

Related Weaknesses (CWE)

CWE-94CWE-617

References

FAQ

What is CVE-2026-41523?

CVE-2026-41523 is a vulnerability with a CVSS score of 7.5 (HIGH). vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, an assert-based security check in vLLM's activation function loading allows any unauthenticated attacker to a...

How severe is CVE-2026-41523?

CVE-2026-41523 has been rated HIGH with a CVSS base score of 7.5/10. Review the CVSS metrics above for detailed severity breakdown.

Is there a patch for CVE-2026-41523?

Check the references section above for vendor advisories and patch information. Affected products include: Vllm Vllm.