CVE-2026-115919ONNX: Out-of-Bounds Read in RNN/GRU/LSTM Shape Inference (Old Opsets, Missing Rank Check)
Updated under an hour ago ()
Does this affect you?
It affects onnx. Add what you run to find out whether that includes you.
No exploitation reported and no EPSS estimate yet.
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.
- CVSS
- 6.2 MEDIUM (v3.1, CNA)CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
- Weakness (CWE)
- CWE-125
- Known exploited
- Not in CISA's KEV catalog
- EPSS (exploitation in the next 30 days)
- Not loaded for this CVE
- Assigned by
- GitHub_M
- NVD analysis
- Awaiting Analysis
- Record last updated
- Oct 26, 2026
- First seen by InfoSec Signals
- Oct 26, 2026
The CVE record on cve.org NVD's entry
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