CVE-2026-115920

ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank

MEDIUM
6.2
CVSS Score
Published: October 26, 2026 at 05:26 PM UTC
Updated: October 26, 2026 at 08:17 PM UTC
1 product affected across 1 vendorONNX

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Severity
MEDIUM6.2
Exploit prediction
EPSS 0.2%
SSVC
No known exploit

Description

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.

Affected

Our own answer: ranges merged, affected separated from platform-only, with confidence and review flags.

1.2.1 ≤ v < 1.22.01.2.1

Remediation

No guide yet

No remediation guidance has been written for this CVE yet, and no fixed version or vendor advisory is recorded against it.

SSVC — Action Prioritization

SSVCNo known exploitNot automatablePartial impact

SSVC signals action urgency (what to patch first), separate from CVSS which measures severity.

CVSS

6.2MEDIUMGitHub_M
Attack Vector
LOCAL
Complexity
LOW
Privileges
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
NONE
Integrity
NONE
Availability
HIGH
Vector?

Quick Info

StatusAWAITING ANALYSIS
CWE
CWE-125

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