{"id":"CVE-2026-115920","aliases":["GHSA-6pwm-x34p-fvj2"],"title":"ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank","titleSource":"GitHub_M","descriptionSource":"OSV","declaredSeverity":"MODERATE","description":"## Summary\n\nONNX ConvTranspose shape inference performed an out-of-bounds read when the weight tensor had fewer than three dimensions and the model did not provide a `kernel_shape` attribute.\n\nThe inference function derived an empty `effective_kernel_shape` vector from the undersized weight tensor, then indexed that vector once for each spatial dimension of the input tensor. A crafted model passed `onnx.checker.check_model()` and caused SIGSEGV when passed to `onnx.shape_inference.infer_shapes()`.\n\n## Technical details\n\nFor an input shape such as `[1, 1, 5]`, shape inference computes one spatial input dimension. A weight shape such as `[1, 3]` has no spatial dimensions, so deriving `kernel_shape` from dimensions 2 onward produces an empty vector. The output loop nevertheless accesses `effective_kernel_shape[0]`.\n\nThe defect affected both the older `convTransposeShapeInference_opset11()` path and the then-current ConvTranspose inference implementation.\n\n## Impact\n\nAn application that performs shape inference on an untrusted model can be terminated, causing denial of service. The observed result was a deterministic process crash. No confidentiality or integrity impact was demonstrated.\n\n## Affected versions\n\n- Affected: ONNX 1.2.1 through 1.21.0\n- Patched: ONNX 1.22.0\n\n## Remediation\n\nUpgrade to ONNX 1.22.0 or later. The fix rejects input and weight tensors with fewer than three dimensions before deriving the spatial kernel shape.\n\n- Fix: [onnx/onnx#7997](https://github.com/onnx/onnx/pull/7997)\n- Commit: [`2ec288908`](https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf)\n\nThe original malformed model was re-tested against the published ONNX 1.23.2 wheel and correctly raises `InferenceError`.\n\n## Severity\n\nThe vulnerable ONNX component processes the malicious model through a local library API or file boundary and is not itself bound to a network stack. Applications that expose ONNX model processing over a network should calculate an Environmental score with Modified Attack Vector set to Network.","severity":"medium","score":6.2,"published":"2026-10-26T17:26:40.506Z","modified":"2026-10-28T21:30:03.915Z","withdrawn":false,"knownExploited":false,"affected":[{"ecosystem":"PyPI","name":"onnx","sources":[{"name":"OSV · GHSA-6pwm-x34p-fvj2","url":"https://osv.dev/vulnerability/GHSA-6pwm-x34p-fvj2"}],"ranges":[{"events":[{"introduced":"1.2.1"},{"fixed":"1.22.0"}],"type":"ECOSYSTEM"}],"versions":["1.10.0","1.10.1","1.10.2","1.11.0","1.12.0","1.13.0","1.13.1","1.14.0","1.14.1","1.15.0","1.16.0","1.16.1","1.16.2","1.17.0","1.18.0","1.19.0","1.19.1","1.19.1rc1","1.2.1","1.2.2","1.2.3","1.20.0","1.20.0rc1","1.20.0rc2","1.20.1","1.20.1rc1","1.21.0","1.21.0rc1","1.21.0rc2","1.21.0rc3","1.21.0rc4","1.22.0rc1","1.22.0rc2","1.3.0","1.4.0","1.4.1","1.5.0","1.6.0","1.7.0","1.8.0","1.8.1","1.9.0"],"fixed":["1.22.0"]}],"sourceAffected":[],"references":["https://github.com/onnx/onnx/security/advisories/GHSA-6pwm-x34p-fvj2","https://github.com/onnx/onnx/pull/7997","https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf","https://github.com/onnx/onnx/releases/tag/v1.22.0","https://nvd.nist.gov/vuln/detail/CVE-2026-115920","https://github.com/onnx/onnx"],"sources":[{"name":"CVE","id":"CVE-2026-115920","modified":"2026-10-26T19:48:35.202Z","url":"https://www.cve.org/CVERecord?id=CVE-2026-115920"},{"name":"OSV","id":"GHSA-6pwm-x34p-fvj2","modified":"2026-10-28T21:30:03.915757861Z","url":"https://osv.dev/vulnerability/GHSA-6pwm-x34p-fvj2"}],"assessments":[{"source":"GitHub_M","vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","score":6.2},{"source":"OSV","vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","score":6.2}],"cve":{"records":[{"id":"CVE-2026-115920","source":"GitHub_M","state":"PUBLISHED","reasons":[],"replacements":[],"disputed":false,"unsupportedWhenAssigned":false,"reserved":"2026-10-23T20:21:45.107Z","published":"2026-10-26T17:26:40.506Z","modified":"2026-10-26T19:48:35.202Z"}],"publishers":[{"name":"GitHub_M","role":"CNA","organizationId":"a0819718-46f1-4df5-94e2-005712e83aaa","modified":"2026-10-26T17:26:40.506Z"},{"name":"CISA-ADP","role":"ADP","organizationId":"134c704f-9b21-4f2e-91b3-4a467353bcc0","modified":"2026-10-26T19:48:35.202Z"}],"references":[{"url":"https://github.com/onnx/onnx/security/advisories/GHSA-6pwm-x34p-fvj2","tags":["x_refsource_CONFIRM"],"source":"GitHub_M"},{"url":"https://github.com/onnx/onnx/pull/7997","tags":["x_refsource_MISC"],"source":"GitHub_M"},{"url":"https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf","tags":["x_refsource_MISC"],"source":"GitHub_M"},{"url":"https://github.com/onnx/onnx/releases/tag/v1.22.0","tags":["x_refsource_MISC"],"source":"GitHub_M"}],"weaknesses":[{"id":"CWE-125","description":"CWE-125: Out-of-bounds Read","source":"GitHub_M"}],"applicability":[],"prioritization":[{"source":"CISA-ADP","type":"SSVC","role":"CISA Coordinator","timestamp":"2026-10-26T19:30:01.679717Z","decisions":[{"name":"Exploitation","value":"none"},{"name":"Automatable","value":"no"},{"name":"Technical Impact","value":"partial"}]}]},"products":[{"vendor":"onnx","name":"onnx","platforms":[],"versions":[{"version":">= 1.2.1, < 1.22.0","status":"affected"}],"cpes":[],"source":"GitHub_M","url":"https://www.cve.org/CVERecord?id=CVE-2026-115920"}],"remediation":[],"observedAt":"2026-10-29T14:59:21.675Z","kev":{"status":"not-listed","checkedAt":"2026-10-31T14:10:32.801Z"},"coverage":[{"source":"NVD","status":"available","checkedAt":"2026-10-28T23:10:35.273Z","attemptedAt":"2026-10-28T23:10:35.273Z"},{"source":"GHSA","status":"available","checkedAt":"2026-10-28T23:10:35.851Z","attemptedAt":"2026-10-28T23:10:35.851Z"},{"source":"EUVD","status":"available","checkedAt":"2026-10-28T23:10:35.710Z","attemptedAt":"2026-10-28T23:10:35.710Z"},{"source":"EPSS","status":"available","checkedAt":"2026-10-28T23:10:35.532Z","attemptedAt":"2026-10-28T23:10:35.532Z"}],"evidence":[{"source":"NVD","id":"CVE-2026-115920","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-115920","modified":"2026-10-26T20:17:52.137","score":6.2,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","checkedAt":"2026-10-28T23:10:35.273Z"},{"source":"FIRST EPSS","id":"CVE-2026-115920","url":"https://www.first.org/epss/","probability":0.00178,"percentile":0.07376,"date":"2026-10-28","checkedAt":"2026-10-28T23:10:35.532Z"},{"source":"ENISA EUVD","id":"EUVD-2026-110041","url":"https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-110041","modified":"Oct 28, 2026, 9:16:42 PM","score":6.2,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","checkedAt":"2026-10-28T23:10:35.710Z"},{"source":"GitHub Advisory Database","id":"GHSA-6pwm-x34p-fvj2","url":"https://github.com/advisories/GHSA-6pwm-x34p-fvj2","modified":"2026-10-28T21:16:43Z","score":6.2,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","checkedAt":"2026-10-28T23:10:35.851Z"}],"aiSummary":{"text":"ONNX versions 1.2.1 through 1.21.0 have an out-of-bounds read vulnerability in ConvTranspose shape inference when the weight tensor has fewer than three dimensions. This can cause a denial of service via a crafted model. The issue is resolved in ONNX 1.22.0.","model":"@cf/meta/llama-3.3-70b-instruct-fp8-fast","generatedAt":"2026-10-30T09:44:20.788Z","sources":[{"name":"CVE","url":"https://www.cve.org/CVERecord?id=CVE-2026-115920"},{"name":"OSV","url":"https://osv.dev/vulnerability/GHSA-6pwm-x34p-fvj2"}]}}