{"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":"2026-10-26T19:48:35.202Z"},"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"}},"adp":[{"metrics":[{"other":{"type":"ssvc","content":{"id":"CVE-2026-115920","role":"CISA Coordinator","options":[{"Exploitation":"none"},{"Automatable":"no"},{"Technical Impact":"partial"}],"version":"2.0.3","timestamp":"2026-10-26T19:30:01.679717Z"}}}],"title":"CISA ADP Vulnrichment","providerMetadata":{"orgId":"134c704f-9b21-4f2e-91b3-4a467353bcc0","shortName":"CISA-ADP","dateUpdated":"2026-10-26T19:48:35.202Z"}}]}}