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#1058 - Fix heap OOB read in convertOnnxWeights by validating element counts #1059

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#1058 - Fix heap OOB read in convertOnnxWeights by validating element counts #1059

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33 changes: 33 additions & 0 deletions WeightsContext.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -240,6 +240,18 @@ bool WeightsContext::convertOnnxWeights(
shape.nbDims = onnxTensor.dims().size();
std::copy_n(onnxTensor.dims().begin(), shape.nbDims, shape.d);

// Reject initializers whose declared shape needs more elements than the source data field actually provides.
auto requireElems = [&](size_t availableElems) -> bool {
size_t const vol = static_cast<size_t>(volume(shape));
if (vol > availableElems)
{
LOG_ERROR("ONNX initializer " << initName << " declares volume " << vol
<< " but only " << availableElems << " data elements are present");
return false;
}
return true;
};

// Priority of importing weights:
// 1. User provided
// 2. External weights
Expand Down Expand Up @@ -339,11 +351,20 @@ bool WeightsContext::convertOnnxWeights(
}
else if (onnxTensor.raw_data().size() > 0)
{
if (static_cast<size_t>(volume(shape)) > onnxTensor.raw_data().size() / sizeof(double))
{
LOG_ERROR("ONNX initializer " << initName << " declares more doubles than raw_data provides");
return false;
}
dataPtr = convertDouble(reinterpret_cast<double const*>(onnxTensor.raw_data().data()), shape);
nbytes = onnxTensor.raw_data().size() / (sizeof(double) / sizeof(float));
}
else if (onnxTensor.double_data().size() > 0)
{
if (!requireElems(static_cast<size_t>(onnxTensor.double_data().size())))
{
return false;
}
dataPtr = convertDouble(onnxTensor.double_data().data(), shape);
if (multiplicationWillOverflow(nbytes, sizeof(float)))
{
Expand Down Expand Up @@ -398,12 +419,24 @@ bool WeightsContext::convertOnnxWeights(
break;
case ::ONNX_NAMESPACE::TensorProto::FLOAT16:
case ::ONNX_NAMESPACE::TensorProto::BFLOAT16:
if (!requireElems(static_cast<size_t>(onnxTensor.int32_data().size())))
{
return false;
}
dataPtr = convertInt32Data<uint16_t>(onnxTensor.int32_data().data(), shape, onnxDtype);
break;
case ::ONNX_NAMESPACE::TensorProto::INT8:
if (!requireElems(static_cast<size_t>(onnxTensor.int32_data().size())))
{
return false;
}
dataPtr = convertInt32Data<int8_t>(onnxTensor.int32_data().data(), shape, onnxDtype);
break;
case ::ONNX_NAMESPACE::TensorProto::BOOL:
if (!requireElems(static_cast<size_t>(onnxTensor.int32_data().size())))
{
return false;
}
dataPtr = convertInt32Data<uint8_t>(onnxTensor.int32_data().data(), shape, onnxDtype);
break;
case ::ONNX_NAMESPACE::TensorProto::INT4:
Expand Down