Advisory record · GHSA-6pwm-x34p-fvj2

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

CVSS 6.2 MediumEPSS 0.0018 · 7th percentile

Published by the GitHub Advisory Database at 28 Oct 2026, 21:16 UTC. agentprime has not analysed this yet, so whether it affects any app is not known.

PackageEcosystemAffectedFixed in
onnxPyPI>=1.2.1, <1.22.01.22.0
Identifiers
GHSA-6pwm-x34p-fvj2 · CVE-2026-115920
Weakness (CWE)
CWE-125
Published
28 Oct 2026
Updated
28 Oct 2026

Machine-written summary

Summary written by Claude Haiku from the source advisory. Not reviewed by a person.

The ONNX package on PyPI, versions 1.2.1 through 1.21.0, has an out-of-bounds read in ConvTranspose shape inference when the weight tensor has fewer than three dimensions and no kernel_shape attribute is given. An attacker who can supply a crafted model to an application that runs shape inference on it can crash the process, causing denial of service; no confidentiality or integrity impact was demonstrated. Upgrade to ONNX 1.22.0 or later.

Written 31 Oct 2026.

Not analysed yet

We haven’t published our analysis of this Advisory yet. Once a person has reviewed it, this page will say what’s vulnerable, what has to be true for your app to be affected, and how to check.

Severity and exploitation

ScoreRatingCVSSVectorSource
6.2 Medium 3.1 CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H CNA (GitHub_M)
  • CISA KEV Not listed.
  • EPSS 0.0018, the 7th percentile, on 5 Nov 2026: FIRST’s estimate of the chance of exploitation in the next 30 days.

Timeline

  1. 31 Oct 2026, 14:07 UTC First seen by agentprime
  2. 31 Oct 2026, 14:07 UTC Confirmed by OSV

Sources

Facts on this page come from the GitHub Advisory Database (CC-BY 4.0), OSV and the other sources listed, as published. We don’t reproduce full advisory descriptions, which can contain exploit code.