CVE-2026-115920
Awaiting Analysis Awaiting Analysis - Queue

ONNX ConvTranspose Shape Inference Denial of Service

Publication date: 2026-10-26

Last updated on: 2026-10-26

Assigner: GitHub, Inc.

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.

CVSS Scores

EPSS Scores

Probability:
Percentile:

Meta Information

Published
2026-10-26
Last Modified
2026-10-26
Generated
2026-10-26
AI Q&A
2026-10-26
EPSS Evaluated
N/A
NVD
CVE-2026-115920
EUVD
EUVD-2026-110041

Affected Vendors & Products

Showing 1 associated CPE
Vendor Product Version / Range
onnx onnx >= 1.2.1, < 1.22.0

Helpful Resources

Exploitability

CWE
CWE Icon
KEV
KEV Icon
CWE ID Description
CWE-125 The product reads data past the end, or before the beginning, of the intended buffer.

Attack-Flow Graph

AI Quick Actions

Instant insights powered by AI
Executive Summary

This vulnerability in ONNX affects ConvTranspose shape inference from versions 1.2.1 to 1.22.0. When a weight tensor has fewer than three dimensions and lacks a kernel_shape attribute, the system incorrectly derives an empty effective_kernel_shape and attempts to access it during spatial dimension calculations. This leads to a crash (SIGSEGV) when processing malicious models, causing denial of service without affecting confidentiality or integrity.

Detection Guidance

This vulnerability affects ONNX versions 1.2.1 through 1.21.0. To detect it, check the installed ONNX version using pip show onnx or python -c 'import onnx; print(onnx.__version__)'. If the version is between 1.2.1 and 1.21.0, the system is vulnerable.

Impact Analysis

An attacker could craft a malicious ONNX model that triggers this flaw, causing the application using ONNX to crash. This results in a denial of service, halting normal operations until the system is restarted. There is no evidence of data theft or modification, but service disruption is possible.

Compliance Impact

This vulnerability primarily impacts availability, which may affect compliance with regulations requiring data accessibility and system reliability. GDPR and HIPAA mandate maintaining service availability and protecting data integrity and confidentiality. While this flaw does not directly compromise data, repeated crashes could lead to violations if service levels are not restored promptly.

Mitigation Strategies

Upgrade ONNX to version 1.22.0 or later. This version includes fixes that prevent crashes from malformed ConvTranspose models. Use pip install --upgrade onnx to update.

Chat Assistant

Ask questions about this CVE
Hi! I’m here to help you understand CVE-2026-115920. Ask me anything about the vulnerability, its impact, or mitigation strategies.
0/70

EPSS Chart