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Medium, CVSS 6.2amended

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

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

What to do

Vendor fix available. Upgrade each affected package to the fixed version on its release line (onnx 1.22.0), redeploy, then verify what is actually installed.

This page has no inventory attached, so it cannot say whether you are affected. A vendor fix is not proof that your deployment is fixed.

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Affected packages

  • PyPI onnx

    Affected
    >= 1.2.1, < 1.22.0
    Fixed in
    1.22.0

Sources

Severity and exploitation
Exploitation
No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.
CVSS
6.2 · CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS
  • CVE-2026-115920: 0.18% estimated exploitation activity in the next 30 days; percentile 7.46 (FIRST EPSS, 2026-11-03). This is a model estimate, not proof of exploitation or customer exposure.
Source description

As published by the source; long descriptions are shortened.

Summary ONNX ConvTranspose shape inference performed an out-of-bounds read when the weight tensor had fewer than three dimensions and the model did not provide a `kernel_shape` attribute. The inference function derived an empty `effective_kernel_shape` vector from the undersized weight tensor, then indexed that vector once for each spatial dimension of the input tensor. A crafted model passed `onnx.checker.check_model()` and caused SIGSEGV when passed to `onnx.shape_inference.infer_shapes()`.

Technical details For an input shape such as `[1, 1, 5]`, shape inference computes one spatial input dimension. A weight shape such as `[1, 3]` has no spatial dimensions, so deriving `kernel_shape` from dimensions 2 onward produces an empty vector. The output loop nevertheless accesses `effective_kernel_shape[0]`. The defect affected both the older `convTransposeShapeInference_opset11()` path and the then-current ConvTranspose inference implementation.

Impact An application that…

Dates and revisions
Published by the source
Last modified by the source
Source last checked
  1. Revision 2 · amended ·

    Amended from osv record GHSA-6pwm-x34p-fvj2

  2. Revision 1 · created ·

    Published from ghsa record GHSA-6pwm-x34p-fvj2

Agent brief

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# Patch Next advisory brief: CVE-2026-115920

Advisory: ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank
IDs: CVE-2026-115920, GHSA-6pwm-x34p-fvj2
Record: https://patchnext.com/advisories/cve-2026-115920 (revision 2, source checked 29 Oct 2026, 06:10 UTC)
Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected.
Severity: Medium (CVSS 6.2)
Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV.
Vendor response: Vendor fix available; fixed versions by package: onnx 1.22.0. A vendor fix does not mean a deployment is fixed.

## Affected components
- PyPI onnx: affected >= 1.2.1, < 1.22.0; fixed in 1.22.0

## Suggested inspection (read-only)
- `python -m pip show onnx`: prints the installed version. Run with the environment that serves production active.

## Supported action
Upgrade each affected component to a fixed version on its release line. For a transitive dependency, upgrade the parent package or add an override or constraint, then regenerate the lockfile. Redeploy every environment that ran an affected version.

## Required regression checks
- Run the test suite and a production build.
- Exercise the features that depend on onnx.
- Repeat the inspection and confirm that only fixed versions remain installed.

## Rollback considerations
- Keep the previous lockfile and deployment artifact. Rolling back reinstates the vulnerable version, so apply any documented mitigation while you fix forward.

## Unresolved questions
- Which deployments run an affected version?
- Exploitation status can change. Check again before lowering the priority.
- Mark the work resolved only after the fixed version is verified in production.

## Sources
- Verified: https://github.com/advisories/GHSA-6pwm-x34p-fvj2 (GitHub-reviewed advisory GHSA-6pwm-x34p-fvj2 lists affected ranges: PyPI onnx >=1.2.1 <=1.21.0)
- Verified: https://osv.dev/vulnerability/GHSA-6pwm-x34p-fvj2 (OSV record GHSA-6pwm-x34p-fvj2 lists affected ranges: PyPI onnx >=1.2.1 <1.22.0 (fixed))

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