CVE-2026-115920ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank
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. From 1.2.1 until 1.22.0, ConvTranspose shape inference processes a weight tensor with fewer than three dimensions without a kernel_shape attribute by deriving an empty effective_kernel_shape and indexing it for the input's spatial dimensions. The flaw affects convTransposeShapeInference_opset11() and the current inference path, and an untrusted model that can pass onnx.checker.check_model() can crash onnx.shape_inference.infer_shapes(), causing denial of service without demonstrated confidentiality or integrity impact. 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
The CVE record is authoritative. Products marked “from the name” were identified from the CNA's free-text names, not a CPE, and are matched less certainly. This product uses the NVD API but is not endorsed or certified by the NVD.