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litert/tensor/arithmetic.h: bounds-check axis and index values before vector subscript #10702

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litert/tensor/arithmetic.h: bounds-check axis and index values before vector subscript #10702

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51 changes: 51 additions & 0 deletions litert/tensor/arithmetic.h
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Original file line number Diff line number Diff line change
Expand Up @@ -589,6 +589,10 @@ Tensor<Mixins...> Pad(Tensor<Mixins...> a, Tensor<Mixins...> b,
if (b_info.buffer) {
const LockedBufferSpan<const int32_t> b_lock =
b_info.buffer->Lock().As<const int32_t>();
if (b_lock.size() < 2 * o_info.shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"Padding buffer size must be at least 2 * input rank.")));
}
const int32_t* b_data = b_lock.data();
for (int i = 0; i < o_info.shape.size(); ++i) {
o_info.shape[i] += b_data[i * 2] + b_data[i * 2 + 1];
Expand Down Expand Up @@ -617,6 +621,10 @@ Tensor<Mixins...> PadV2(Tensor<Mixins...> a, Tensor<Mixins...> b,
if (b_info.buffer) {
const LockedBufferSpan<const int32_t> b_lock =
b_info.buffer->Lock().As<const int32_t>();
if (b_lock.size() < 2 * o_info.shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"Padding buffer size must be at least 2 * input rank.")));
}
const int32_t* b_data = b_lock.data();
for (int i = 0; i < o_info.shape.size(); ++i) {
o_info.shape[i] += b_data[i * 2] + b_data[i * 2 + 1];
Expand Down Expand Up @@ -800,9 +808,19 @@ Tensor<Mixins...> Sum(Tensor<Mixins...> a, Tensor<Mixins...> b, bool keep_dims,
if (op->keep_dims) {
o_info.shape = a_info.shape;
if (b_info.shape.empty()) {
if (b_data[0] < 0 ||
static_cast<size_t>(b_data[0]) >= o_info.shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"The reduction axis is out of range.")));
}
o_info.shape.push_back(o_info.shape[b_data[0]]);
} else {
for (int i = 0; i < b_info.shape[0]; ++i) {
if (b_data[i] < 0 ||
static_cast<size_t>(b_data[i]) >= o_info.shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"The reduction axis is out of range.")));
}
o_info.shape[b_data[i]] = 1;
}
}
Expand Down Expand Up @@ -860,9 +878,19 @@ Tensor<Mixins...> ReduceMax(Tensor<Mixins...> a, Tensor<Mixins...> b,
if (op->keep_dims) {
o_info.shape = a_info.shape;
if (b_info.shape.empty()) {
if (b_data[0] < 0 ||
static_cast<size_t>(b_data[0]) >= o_info.shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"The reduction axis is out of range.")));
}
o_info.shape.push_back(o_info.shape[b_data[0]]);
} else {
for (int i = 0; i < b_info.shape[0]; ++i) {
if (b_data[i] < 0 ||
static_cast<size_t>(b_data[i]) >= o_info.shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"The reduction axis is out of range.")));
}
o_info.shape[b_data[i]] = 1;
}
}
Expand Down Expand Up @@ -919,9 +947,19 @@ Tensor<Mixins...> Mean(Tensor<Mixins...> a, Tensor<Mixins...> b, bool keep_dims,
if (op->keep_dims) {
o_info.shape = a_info.shape;
if (b_info.shape.empty()) {
if (b_data[0] < 0 ||
static_cast<size_t>(b_data[0]) >= o_info.shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"The reduction axis is out of range.")));
}
o_info.shape.push_back(o_info.shape[b_data[0]]);
} else {
for (int i = 0; i < b_info.shape[0]; ++i) {
if (b_data[i] < 0 ||
static_cast<size_t>(b_data[i]) >= o_info.shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"The reduction axis is out of range.")));
}
o_info.shape[b_data[i]] = 1;
}
}
Expand Down Expand Up @@ -1374,6 +1412,10 @@ Tensor<Mixins...> Concatenation(
graph::TensorInformation& output_info = *GetInfo(output.GetRaw());
output_info.type = first_input_info.type;
output_info.shape = first_input_info.shape;
if (axis < 0 || axis >= static_cast<int>(first_input_info.shape.size())) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"The Concatenation axis is out of range.")));
}
for (size_t i = 1; i < inputs.size(); ++i) {
const graph::TensorInformation& input_info = *GetInfo(inputs[i].GetRaw());
output_info.shape[axis] += input_info.shape[axis];
Expand Down Expand Up @@ -1583,8 +1625,17 @@ Tensor<Mixins...> Transpose(Tensor<Mixins...> input, Tensor<Mixins...> perm,
if (perm_info.buffer) {
const auto perm_data = perm_info.buffer->Lock().As<const int32_t>();
const auto& input_shape = input_info.shape;
if (perm_data.size() != input_shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"Transpose permutation length must equal input rank.")));
}
output_info.shape.resize(input_shape.size());
for (size_t i = 0; i < perm_data.size(); ++i) {
if (perm_data.data()[i] < 0 ||
static_cast<size_t>(perm_data.data()[i]) >= input_shape.size()) {
return Tensor<Mixins...>(graph::ErrorTensor(absl::InvalidArgumentError(
"Transpose permutation value is out of range.")));
}
output_info.shape[i] = input_shape[perm_data.data()[i]];
}
} else {
Expand Down