vLLM: Security Check Bypass via assert Statement in Activation Function Loading Allows Arbitrary Code Execution
Summary
| CVE | CVE-2026-41523 |
|---|---|
| State | PUBLISHED |
| Assigner | GitHub_M |
| Source Priority | CVE Program / NVD first with legacy fallback |
| Published | 2026-06-22 23:16:30 UTC |
| Updated | 2026-09-02 13:17:45 UTC |
| 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. |
Risk And Classification
Primary CVSS: v3.1 7.5 HIGH from ADP
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS: 0.009130000 probability, percentile 0.576780000 (date 2026-09-02)
Problem Types: CWE-94 | CWE-617 | CWE-94 CWE-94: Improper Control of Generation of Code ('Code Injection') | CWE-617 CWE-617: Reachable Assertion | CWE-617 Reachable Assertion
| Version | Source | Type | Score | Severity | Vector |
|---|---|---|---|---|---|
| 3.1 | ADP | CVSS | 7.5 | HIGH | CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H |
| 3.1 | [email protected] | Secondary | 7.5 | HIGH | CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H |
| 3.1 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | Secondary | 7.5 | HIGH | CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H |
| 3.1 | CNA | DECLARED | 7.5 | HIGH | CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H |
CVSS v3.1 Breakdown
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
NVD Known Affected Configurations (CPE 2.3)
Vendor Declared Affected Products
| Source | Vendor | Product | Version | Platforms |
|---|---|---|---|---|
| CNA | Vllm-project | Vllm | affected < 0.22.0 | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.2 | unaffected 1782951012 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.2 | unaffected 1787860580 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.2 | unaffected 1782951244 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.2 | unaffected 1787884873 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.3 | unaffected 1787161382 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.3 | unaffected 1787161803 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.4 | unaffected 1787151769 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.4 | unaffected 1787151840 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.4 | unaffected 1787151771 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server 3.4 | unaffected 1787151774 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.3 | unaffected 1788273908 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.3 | unaffected 1788273909 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.3 | unaffected 1788273908 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.3 | unaffected 1788260684 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.3 | unaffected 1788273977 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.3 | unaffected 1788260620 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.4 | unaffected 1787310717 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.4 | unaffected 1787253912 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.4 | unaffected 1787253989 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.4 | unaffected 1787254059 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.4 | unaffected 1787243961 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.4 | unaffected 1787253774 * rpm | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI 3.4 | unaffected 1787244006 * rpm | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
References
| Reference | Source | Link | Tags |
|---|---|---|---|
| access.redhat.com/errata/RHSA-2026:59144 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| access.redhat.com/errata/RHSA-2026:62336 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| access.redhat.com/errata/RHSA-2026:57390 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| access.redhat.com/errata/RHSA-2026:57387 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| github.com/vllm-project/vllm/security/advisories/GHSA-q8gq-377p-jq3r | [email protected] | github.com | Exploit, Third Party Advisory |
| access.redhat.com/errata/RHSA-2026:61627 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| huntr.com/bounties/dcb05b04-e625-41e7-adbc-bbae0cc2d64c | [email protected] | huntr.com | Third Party Advisory |
| access.redhat.com/errata/RHSA-2026:59151 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| access.redhat.com/errata/RHSA-2026:59139 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| access.redhat.com/errata/RHSA-2026:57380 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-41523.json | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | security.access.redhat.com | |
| access.redhat.com/errata/RHSA-2026:36006 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| access.redhat.com/errata/RHSA-2026:59138 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| access.redhat.com/errata/RHSA-2026:61629 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| bugzilla.redhat.com/show_bug.cgi | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | bugzilla.redhat.com | |
| github.com/vllm-project/vllm/commit/b3c7ffcab82c2439726f8cb213800f6f38c0... | [email protected] | github.com | Patch |
| access.redhat.com/errata/RHSA-2026:36005 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| access.redhat.com/errata/RHSA-2026:57389 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| access.redhat.com/security/cve/CVE-2026-41523 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| CVE Program record | CVE.ORG | www.cve.org | canonical |
| NVD vulnerability detail | NVD | nvd.nist.gov | canonical, analysis |
Additional Advisory Data
| Source | Time | Event |
|---|---|---|
| ADP | 2026-06-22T23:01:00.799Z | Reported to Red Hat. |
| ADP | 2026-06-22T22:18:14.494Z | Made public. |
Solutions
ADP: RHSA-2026:61627: Red Hat AI Inference Server 3.2
ADP: RHSA-2026:36005: Red Hat AI Inference Server 3.2
ADP: RHSA-2026:61629: Red Hat AI Inference Server 3.2
ADP: RHSA-2026:36006: Red Hat AI Inference Server 3.2
ADP: RHSA-2026:59138: Red Hat AI Inference Server 3.3
ADP: RHSA-2026:59139: Red Hat AI Inference Server 3.3
ADP: RHSA-2026:57380: Red Hat AI Inference Server 3.4
ADP: RHSA-2026:57389: Red Hat AI Inference Server 3.4
ADP: RHSA-2026:57390: Red Hat AI Inference Server 3.4
ADP: RHSA-2026:57387: Red Hat AI Inference Server 3.4
ADP: RHSA-2026:62336: Red Hat Enterprise Linux AI 3.3
ADP: RHSA-2026:59151: Red Hat Enterprise Linux AI 3.4
ADP: RHSA-2026:59144: Red Hat Enterprise Linux AI 3.4
Workarounds
ADP: Avoid running vLLM with python -O or PYTHONOPTIMIZE=1 until updated packages are available. Only load models from trusted sources. Restrict who can deploy or update models on inference endpoints. Apply network access controls and authentication in front of vLLM APIs.