CVE-2026-115919MediumMicrosoft CVSS 6.2CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H/E:U

Microsoft security update for CVE-2026-115919 — azl3 pytorch 2.2.2-17 on Azure Linux 3.0

Published
October 31, 2026
Last Modified
—

🔗 CVE IDs covered (1)

📋 Microsoft's advisory

EchelonGraph does not copy Microsoft's advisory page: its FAQ and remediation text are not shown here. Read the advisory on https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-115919. This page also shows what EchelonGraph holds for CVE-2026-115919, with the description from its CVE record, which the CVE Numbering Authority that assigned the CVE wrote: for a CVE Microsoft assigned, often in the words of Microsoft's own advisory.

🎯 Affected products1

  • azl3 pytorch 2.2.2-17 on Azure Linux 3.0

✅ Updates Microsoft lists: 1 update

1 row: one per KB article or update, update type and fixed build. Their details are on Microsoft's advisory.

KB articleUpdateFixed build
—Security Update—

🧭 EchelonGraph on CVE-2026-115919

EchelonGraph score
6.2 MEDIUM
CISA KEV
Not listed
Fix status
A fix is available — apply it.

Description from the CVE record (CVE.org), as published by its numbering authority

Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to 1.22.0, RNNShapeInference_opset1_to_6() processes malformed RNN and LSTM nodes from opsets 1 through 6 and GRU nodes from opsets 3 through 6 without verifying that the first input has rank three. The function accesses dim(0) and dim(1) on an undersized protobuf shape, which can read outside the intended repeated field and terminate an application when onnx.shape_inference.infer_shapes() processes an untrusted model that can pass onnx.checker.check_model(). This issue is fixed in version 1.22.0.

Published by GitHub, Inc., the CVE Numbering Authority that assigned CVE-2026-115919, in its CVE record at CVE.org; reused under the CVE Program's Terms of Use (its licence and MITRE's copyright notice are in our Terms of Service).

🔗 References (2)