{"dataType": "CVE_RECORD", "dataVersion": "5.2", "cveMetadata": {"cveId": "CVE-2026-115920", "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "state": "PUBLISHED", "assignerShortName": "GitHub_M", "dateReserved": "2026-10-23T20:21:45.107Z", "datePublished": "2026-10-26T17:26:40.506Z", "dateUpdated": "2026-10-26T17:26:40.506Z"}, "containers": {"cna": {"title": "ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank", "problemTypes": [{"descriptions": [{"cweId": "CWE-125", "lang": "en", "description": "CWE-125: Out-of-bounds Read", "type": "CWE"}]}], "metrics": [{"cvssV3_1": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "HIGH", "baseScore": 6.2, "baseSeverity": "MEDIUM", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H", "version": "3.1"}}], "references": [{"name": "https://github.com/onnx/onnx/security/advisories/GHSA-6pwm-x34p-fvj2", "tags": ["x_refsource_CONFIRM"], "url": "https://github.com/onnx/onnx/security/advisories/GHSA-6pwm-x34p-fvj2"}, {"name": "https://github.com/onnx/onnx/pull/7997", "tags": ["x_refsource_MISC"], "url": "https://github.com/onnx/onnx/pull/7997"}, {"name": "https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf", "tags": ["x_refsource_MISC"], "url": "https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf"}, {"name": "https://github.com/onnx/onnx/releases/tag/v1.22.0", "tags": ["x_refsource_MISC"], "url": "https://github.com/onnx/onnx/releases/tag/v1.22.0"}], "affected": [{"vendor": "onnx", "product": "onnx", "versions": [{"version": ">= 1.2.1, < 1.22.0", "status": "affected"}]}], "providerMetadata": {"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M", "dateUpdated": "2026-10-26T17:26:40.506Z"}, "descriptions": [{"lang": "en", "value": "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."}], "source": {"advisory": "GHSA-6pwm-x34p-fvj2", "discovery": "UNKNOWN"}}}}

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