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[Tensorflow] Fix potential vulnerable cloned function #1015

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[Tensorflow] Fix potential vulnerable cloned function #1015

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43 changes: 43 additions & 0 deletions tensorflow/core/kernels/quantize_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -113,7 +113,50 @@ class QuantizeV2Op : public OpKernel {

int num_slices = 1;
if (axis_ > -1) {
OP_REQUIRES(
ctx, input.dims() > axis_,
errors::InvalidArgument(
"Axis is on a zero-based index, so its value must always be less "
"than number of input's dims, but given axis value was ",
axis_, " and input's dims was ", input.dims()));
num_slices = input.dim_size(axis_);
OP_REQUIRES(ctx, input_min_range.dims() == 1,
errors::InvalidArgument(
"If axis is specified, min_range must be a 1-D tensor "
"whose size matches the axis dimension of the input and "
"output tensors, but min_range dims are ",
input_min_range.dims()));
OP_REQUIRES(ctx, input_min_range.dim_size(0) == num_slices,
errors::InvalidArgument(
"If axis is specified, min_range must be a 1-D tensor "
"whose size matches the axis dimension of the input and "
"output tensors, but min_range is a 1-D tensor of size ",
input_min_range.dim_size(0),
" and input's axis dimension is of size ", num_slices));
OP_REQUIRES(ctx, input_max_range.dims() == 1,
errors::InvalidArgument(
"If axis is specified, max_range must be a 1-D tensor "
"whose size matches the axis dimension of the input and "
"output tensors, but max_range dims are ",
input_max_range.dims()));
OP_REQUIRES(ctx, input_max_range.dim_size(0) == num_slices,
errors::InvalidArgument(
"If axis is specified, max_range must be a 1-D tensor "
"whose size matches the axis dimension of the input and "
"output tensors, but max_range is a 1-D tensor of size ",
input_max_range.dim_size(0),
" and input's axis dimension is of size ", num_slices));
} else {
OP_REQUIRES(ctx, input_min_range.NumElements() == 1,
errors::InvalidArgument(
"If axis is not specified, min_range must contain a "
"single float element, but it contains ",
input_min_range.NumElements(), " elements"));
OP_REQUIRES(ctx, input_max_range.NumElements() == 1,
errors::InvalidArgument(
"If axis is not specified, max_range must contain a "
"single float element, but it contains ",
input_max_range.NumElements(), " elements"));
}

const TensorShape& minmax_shape = ctx->input(1).shape();
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