# CVE-2026-115920: ONNX ConvTranspose shape inference denial of service

Source: https://junglewise.ai/threats/cve-2026-115920-open-neural-network-exchange-onnx-is-an-open-standard-for  
Publisher: Junglewise Threat Intelligence, https://junglewise.ai/threats  
Published: 2026-10-26. Updated: 2026-10-26  
License: CC BY 4.0 with a link back

CVE-2026-115920 · Severity: medium · CVSS 6.2 · Published 2026-10-26

ONNX is an open standard format for machine learning models. A flaw in shape inference for the ConvTranspose operator can cause the shape inference function to crash when processing a malformed model file, disrupting model loading and processing pipelines without exposing data or compromising system integrity.

Technologies: [ONNX](https://junglewise.ai/threats/technologies/onnx-onnx), [onnx (PyPI)](https://junglewise.ai/threats/technologies/onnx). Vendors: [ONNX](https://junglewise.ai/threats/vendors/onnx), [PyPI](https://junglewise.ai/threats/vendors/pypi).

## Quick answers

**Is CVE-2026-115920 exploited in the wild?** No. Junglewise Threat Intelligence has no report of CVE-2026-115920 being exploited in the wild.

**How severe is CVE-2026-115920?** Medium severity, with a CVSS score of 6.2, published 26 October 2026.

**Which products and versions are affected?** ONNX 1.2.1 through 1.21.x; onnx (PyPI) >= 1.2.1, <= 1.21.0, ECOSYSTEM:introduced=1.2.1,fixed=1.22.0.

**Is there a fix for CVE-2026-115920?** Yes. onnx (PyPI): upgrade to 1.22.0 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.

**How is CVE-2026-115920 attacked?** It is attacked over the network, in a software library.

**Am I affected by CVE-2026-115920?** Check whether you run ONNX or onnx (PyPI) at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

## How to fix

- onnx (PyPI): upgrade to 1.22.0 or later

  ```sh
  pip install "onnx>=1.22.0"
  ```


## Technical details

The vulnerability exists in convTransposeShapeInference_opset11() which processes a weight tensor with fewer than three dimensions and no kernel_shape attribute, deriving an empty effective_kernel_shape and then indexing it with the input's spatial dimensions, causing an out-of-bounds access. An untrusted ONNX model that passes model validation can trigger a crash in onnx.shape_inference.infer_shapes(), leading to denial of service. The fix adds explicit validation to ensure input and weight tensors have minimum required dimensions before shape inference.

## Affected products

- ONNX ONNX 1.2.1 through 1.21.x

## Identifiers

- CVE-2026-115920
- GHSA-6pwm-x34p-fvj2

## Timeline

- 2026-10-26: disclosed
- 2026-05-19: patched: Fix committed to main branch

## References

- [https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf](https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf)
- [https://github.com/onnx/onnx/pull/7997](https://github.com/onnx/onnx/pull/7997)

## Related threats

- [ONNX memory exhaustion in packed tensor unpacking](https://junglewise.ai/threats/cve-2026-115922-open-neural-network-exchange-onnx-is-an-open-standard-for)
- [ONNX null pointer dereference in shape inference](https://junglewise.ai/threats/cve-2026-115921-open-neural-network-exchange-onnx-is-an-open-standard-for)
- [ONNX out-of-bounds read in RNN shape inference](https://junglewise.ai/threats/cve-2026-115919-open-neural-network-exchange-onnx-is-an-open-standard-for)
- [ONNX TOCTOU race condition in save_external_data](https://junglewise.ai/threats/onnx-toctou-race-condition-in-save-external-data-b85422b8)
- [ONNX save_external_data symlink-following file write](https://junglewise.ai/threats/cve-2026-49114-onnx-save-external-data-symlink-following-file-write)