CVE-2026-115920

Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.2.1 until 1.22.0, ConvTranspose shape inference processes a weight tensor with fewer than three dimensions without a kernel_shape attribute by deriving an empty effective_kernel_shape and indexing it for the input's spatial dimensions. The flaw affects convTransposeShapeInference_opset11() and the current inference path, and an untrusted model that can pass onnx.checker.check_model() can crash onnx.shape_inference.infer_shapes(), causing denial of service without demonstrated confidentiality or integrity impact. This issue is fixed in version 1.22.0.

CVSS v3 6.2 MEDIUM

6.2^/10

CVSS v3 : MEDIUM

Vector :

Exploitability : 2.5 / Impact : 3.6

Attack Vector LOCAL

Attack Complexity LOW

Privileges Required NONE

User Interaction NONE

Confidentiality Impact NONE

Integrity Impact NONE

Availability Impact HIGH

Scope UNCHANGED

References

Link	Resource
https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf
https://github.com/onnx/onnx/pull/7997
https://github.com/onnx/onnx/releases/tag/v1.22.0
https://github.com/onnx/onnx/security/advisories/GHSA-6pwm-x34p-fvj2

Configurations

No configuration.

History

26 Oct 2026, 18:17

Type	Values Removed	Values Added
New CVE

Information

Published : 2026-10-26 18:17

Updated : 2026-10-26 20:17

NVD link : CVE-2026-115920

Mitre link : CVE-2026-115920

CVE.ORG link : CVE-2026-115920

JSON object : View

Products Affected

No product.

CWE

CWE-125

Out-of-bounds Read

{"id": "CVE-2026-115920", "cveTags": [], "metrics": {"ssvcV203": [{"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "ssvcData": {"id": "CVE-2026-115920", "role": "CISA Coordinator", "options": [{"exploitation": "none"}, {"automatable": "no"}, {"technicalImpact": "partial"}], "version": "2.0.3", "timestamp": "2026-10-26T19:30:01.679717Z"}}], "cvssMetricV31": [{"type": "Secondary", "source": "security-advisories@github.com", "cvssData": {"scope": "UNCHANGED", "version": "3.1", "baseScore": 6.2, "attackVector": "LOCAL", "baseSeverity": "MEDIUM", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H", "integrityImpact": "NONE", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "HIGH", "privilegesRequired": "NONE", "confidentialityImpact": "NONE"}, "impactScore": 3.6, "exploitabilityScore": 2.5}]}, "affected": [{"source": "security-advisories@github.com", "affectedData": [{"vendor": "onnx", "product": "onnx", "versions": [{"status": "affected", "version": ">= 1.2.1, < 1.22.0"}]}]}], "published": "2026-10-26T18:17:39.800", "references": [{"url": "https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf", "source": "security-advisories@github.com"}, {"url": "https://github.com/onnx/onnx/pull/7997", "source": "security-advisories@github.com"}, {"url": "https://github.com/onnx/onnx/releases/tag/v1.22.0", "source": "security-advisories@github.com"}, {"url": "https://github.com/onnx/onnx/security/advisories/GHSA-6pwm-x34p-fvj2", "source": "security-advisories@github.com"}], "vulnStatus": "Awaiting Analysis", "weaknesses": [{"type": "Secondary", "source": "security-advisories@github.com", "description": [{"lang": "en", "value": "CWE-125"}]}], "descriptions": [{"lang": "en", "value": "Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.2.1 until 1.22.0, ConvTranspose shape inference processes a weight tensor with fewer than three dimensions without a kernel_shape attribute by deriving an empty effective_kernel_shape and indexing it for the input's spatial dimensions. The flaw affects convTransposeShapeInference_opset11() and the current inference path, and an untrusted model that can pass onnx.checker.check_model() can crash onnx.shape_inference.infer_shapes(), causing denial of service without demonstrated confidentiality or integrity impact. This issue is fixed in version 1.22.0."}], "lastModified": "2026-10-26T20:17:52.137", "sourceIdentifier": "security-advisories@github.com"}