Description
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.3.0 until 1.22.0, onnx.version_converter.convert_version() can perform an out-of-bounds read in Gemm_7_6::adapt_gemm_7_6() in onnx/version_converter/adapters/gemm_7_6.h when a Gemm node has input tensors with fewer than two dimensions because B_shape[1], A_shape[0], or A_shape[1] is accessed without a rank check, potentially causing a process crash during an opset 7 to 6 downgrade. This issue is fixed in version 1.22.0.
Published: 2026-08-18
Score: 3.3 Low
EPSS: < 1% Very Low
KEV: No
Impact: n/a
Action: n/a
AI Analysis

Impact

The vulnerability is an out‑of‑bounds read in the Gemm adapter during a version downgrade from opset 7 to 6. When a Gemm node has fewer than two input dimensions, the conversion routine accesses B_shape[1], A_shape[0] or A_shape[1] without checking rank, which can cause the process to crash. The weakness that enables this is a heap memory access error, identified as CWE‑125, leading to a denial of service rather than to code execution or confidentiality loss.

Affected Systems

The affected component is the ONNX library, version 1.3.0 through 1.21.x. Any installation that performs a version conversion using onnx.version_converter.convert_version() and includes Gemm nodes with undersized input tensors is at risk. The issue was resolved in ONNX 1.22.0 and later releases.

Risk and Exploitability

The CVSS score is 3.3, indicating low severity. No EPSS score is available, and the vulnerability is not listed in CISA’s Known Exploited Vulnerabilities catalog. The attack vector is inferred to be local or application‑controlled, as the crash occurs when an onnx.version_converter call is made with improperly shaped data. An attacker who can drive the conversion process, such as a malicious user of an ML service that performs opset downgrades, could force a crash and cause a denial of service.

Generated by OpenCVE AI on August 18, 2026 at 16:41 UTC.

Remediation

No vendor fix or workaround currently provided.

OpenCVE Recommended Actions

  • Upgrade the ONNX library to version 1.22.0 or later to ensure the fix is applied
  • Verify that all Gemm nodes in any ONNX models have tensors with at least two dimensions before performing a version downgrade
  • Monitor application logs for unexpected crashes during opset conversion and apply the above patches promptly

Generated by OpenCVE AI on August 18, 2026 at 16:41 UTC.

Tracking

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Advisories
Source ID Title
Github GHSA Github GHSA GHSA-p893-rvq9-2xf9 ONNX: Heap-Buffer-Overflow READ in Gemm Version Converter Adapter via Undersized Input Shape
History

Thu, 27 Aug 2026 18:00:00 +0000

Type Values Removed Values Added
References
Metrics threat_severity

None

threat_severity

Low


Tue, 18 Aug 2026 19:30:00 +0000

Type Values Removed Values Added
Metrics ssvc

{'options': {'Automatable': 'no', 'Exploitation': 'poc', 'Technical Impact': 'partial'}, 'version': '2.0.3'}


Tue, 18 Aug 2026 18:00:00 +0000

Type Values Removed Values Added
First Time appeared Onnx
Onnx onnx
Vendors & Products Onnx
Onnx onnx

Tue, 18 Aug 2026 15:15:00 +0000

Type Values Removed Values Added
Description Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.3.0 until 1.22.0, onnx.version_converter.convert_version() can perform an out-of-bounds read in Gemm_7_6::adapt_gemm_7_6() in onnx/version_converter/adapters/gemm_7_6.h when a Gemm node has input tensors with fewer than two dimensions because B_shape[1], A_shape[0], or A_shape[1] is accessed without a rank check, potentially causing a process crash during an opset 7 to 6 downgrade. This issue is fixed in version 1.22.0.
Title ONNX: Heap-Buffer-Overflow READ in Gemm Version Converter Adapter via Undersized Input Shape
Weaknesses CWE-125
References
Metrics cvssV3_1

{'score': 3.3, 'vector': 'CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L'}


cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published:

Updated: 2026-08-18T18:51:29.068Z

Reserved: 2026-07-17T14:11:15.482Z

Link: CVE-2026-63632

cve-icon Vulnrichment

Updated: 2026-08-18T18:51:10.677Z

cve-icon NVD

Status : Received

Published: 2026-08-18T15:16:56.463

Modified: 2026-08-18T19:16:59.787

Link: CVE-2026-63632

cve-icon Redhat

Severity : Low

Publid Date: 2026-08-18T14:55:15Z

Links: CVE-2026-63632 - Bugzilla

cve-icon OpenCVE Enrichment

Updated: 2026-08-18T17:45:06Z

Weaknesses