CVE-2026-115920: medium-severity vulnerability in onnx
ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank
Published
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13Vexday Risk Score
No sign of exploitation. No public exploitation artifact known so far.
ssvc Trackcvss 6.2epss 0.2%
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:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Affected products
onnx · onnxRelated CVEs — onnx
In the same product, most dangerous first.
CVE-2024-27318HIGHCVE-2024-27318EPSS 1.2%CVE-2026-27489HIGHONNX: Path Traversal via SymlinkEPSS 0.6%CVE-2024-27319MEDIUMCVE-2024-27319EPSS 0.6%CVE-2026-28500HIGHONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain AttackEPSS 0.3%CVE-2026-34445HIGHONNX: Malicious ONNX models can crash servers by exploiting unprotected object settings.EPSS 0.3%CVE-2026-34447MEDIUMONNX: External Data Symlink TraversalEPSS 0.3%