{"id":"ghsa-ghsa-q69g-f4f5-v8m7","seq":2056921,"kind":"advisory","title":"ONNX: Denial of service via unchecked expansion of packed sub-byte tensors in ONNX Python APIs","url":"https://github.com/advisories/GHSA-q69g-f4f5-v8m7","permalink":"https://vulnpulse.app/items/ghsa-ghsa-q69g-f4f5-v8m7","summary":"影響: pip:onnx <= 1.21.0 → 1.22.0\nONNX's Python tensor-materialization helpers could allocate memory according to attacker-controlled tensor dimensions without verifying that a packed sub-byte payload contained the declared number of elements. A very small model could therefore cause a disproportionately large allocation when an application called onnx.numpy_helper.to_array() or constructed onnx.reference.ReferenceEvaluator with the model. The issue affected UINT2, INT2, UINT4, INT4, and FLOAT4E2M1 tensors stored in either raw_…","severity":"medium","techs":["python"],"cves":["CVE-2026-115922"],"tags":["GHSA-q69g-f4f5-v8m7","onnx"],"source":{"id":"ghsa","name":"GitHub Advisory Database"},"published_at":"2026-10-28T21:16:37.000Z","fetched_at":"2026-10-29T00:48:52.653Z"}