CVE-2026-115921Medium· 6.2▾ SunlitOpen Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.4.0 until 1.22.0, ScanInferenceFunction, ScanInferenceFunction_opset8, and ScanInferenceFunction_opset9 do not safely validate the requ…
▾ Sunlit zone — Low / medium · no exploitation signal
impact 34.1 · likelihood 0 · exploitation 0
Need a working PoC? Pro members can cast a request and our team develops one — it lands right here.
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.4.0 until 1.22.0, ScanInferenceFunction, ScanInferenceFunction_opset8, and ScanInferenceFunction_opset9 do not safely validate the required num_scan_inputs attribute. A missing attribute is dereferenced as a null pointer, while a negative value is converted to size_t and can reach an exceptional oversized allocation path. An untrusted model can therefore terminate or disrupt shape inference, including a negative-value model that can pass onnx.checker.check_model(). This issue is fixed in version 1.22.0.
onnx >= 1.4.0, < 1.22.0Refer to the linked advisories for vendor-supplied fixes and affected version ranges.
Connected by shared product, vendor, weakness, or advisory.
CVE-2026-44512Medium· 5.5ONNX has Null Pointer Dereference in Upsample Version Converter Adapter (Zero Inputs)
CVE-2026-115919Medium· 6.2ONNX: Out-of-Bounds Read in RNN/GRU/LSTM Shape Inference (Old Opsets, Missing Rank Check)
CVE-2026-115920Medium· 6.2ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank
CVE-2026-115922Medium· 6.2ONNX: Denial of service via unchecked expansion of packed sub-byte tensors in ONNX Python APIs
CVE-2026-63632Low· 3.3Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability
CVE-2024-27318High· 7.5Onnx Directory Traversal vulnerability