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Fix stack exhaustion DoS in json parsing via iterative shape traversal #4138

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Fix stack exhaustion DoS in json parsing via iterative shape traversal #4138

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34 changes: 25 additions & 9 deletions tensorflow_serving/util/json_tensor.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -346,13 +346,25 @@ Status AddValueToTensor(const rapidjson::Value& val, DataType dtype,
// `val` can be scalar or list or list of lists with arbitrary nesting. If a
// scalar (non array) is passed, we do not add dimension info to shape (as
// scalars do not have a dimension).
void GetDenseTensorShape(const rapidjson::Value& val, TensorShapeProto* shape) {
if (!val.IsArray()) return;
const auto size = val.Size();
shape->add_dim()->set_size(size);
if (size > 0) {
GetDenseTensorShape(val[0], shape);
constexpr int kMaxTensorRank = 254;

Status GetDenseTensorShape(const rapidjson::Value& val, TensorShapeProto* shape) {
const rapidjson::Value* curr = &val;
int depth = 0;
while (curr->IsArray()) {
if (++depth > kMaxTensorRank) {
return errors::InvalidArgument(
"Tensor rank exceeds maximum allowed rank: ", kMaxTensorRank);
}
const auto size = curr->Size();
shape->add_dim()->set_size(size);
if (size > 0) {
curr = &((*curr)[0]);
} else {
break;
}
}
return OkStatus();
}

bool IsValBase64Object(const rapidjson::Value& val) {
Expand Down Expand Up @@ -392,6 +404,10 @@ Status JsonDecodeBase64Object(const rapidjson::Value& val,
Status FillTensorProto(const rapidjson::Value& val, int level, DataType dtype,
int* val_count, TensorProto* tensor) {
const auto rank = tensor->tensor_shape().dim_size();
if (rank > kMaxTensorRank) {
return errors::InvalidArgument(
"Tensor rank ", rank, " exceeds maximum allowed rank ", kMaxTensorRank);
}
if (!val.IsArray()) {
// DOM tree for a (dense) tensor will always have all values
// at same (leaf) level equal to the rank of the tensor.
Expand Down Expand Up @@ -453,7 +469,7 @@ Status AddInstanceItem(const rapidjson::Value& item, const string& name,
const auto dtype = tensorinfo_map.at(name).dtype();
auto* tensor = &(*tensor_map)[name];
tensor->mutable_tensor_shape()->Clear();
GetDenseTensorShape(item, tensor->mutable_tensor_shape());
TF_RETURN_IF_ERROR(GetDenseTensorShape(item, tensor->mutable_tensor_shape()));
TF_RETURN_IF_ERROR(
FillTensorProto(item, 0 /* level */, dtype, &size, tensor));
if (!size_map->count(name)) {
Expand Down Expand Up @@ -623,7 +639,7 @@ Status FillTensorMapFromInputsMap(

auto* tensor = &(*tensor_map)[tensorinfo_map.begin()->first];
tensor->set_dtype(tensorinfo_map.begin()->second.dtype());
GetDenseTensorShape(val, tensor->mutable_tensor_shape());
TF_RETURN_IF_ERROR(GetDenseTensorShape(val, tensor->mutable_tensor_shape()));
int unused_size = 0;
TF_RETURN_IF_ERROR(FillTensorProto(val, 0 /* level */, tensor->dtype(),
&unused_size, tensor));
Expand All @@ -639,7 +655,7 @@ Status FillTensorMapFromInputsMap(
auto* tensor = &(*tensor_map)[name];
tensor->set_dtype(dtype);
tensor->mutable_tensor_shape()->Clear();
GetDenseTensorShape(item->value, tensor->mutable_tensor_shape());
TF_RETURN_IF_ERROR(GetDenseTensorShape(item->value, tensor->mutable_tensor_shape()));
int unused_size = 0;
TF_RETURN_IF_ERROR(FillTensorProto(item->value, 0 /* level */, dtype,
&unused_size, tensor));
Expand Down
19 changes: 19 additions & 0 deletions tensorflow_serving/util/json_tensor_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -118,6 +118,25 @@ TEST(JsontensorTest, DeeplyNestedMalformed) {
EXPECT_THAT(status.message(), HasSubstr("key must be a string value"));
}

TEST(JsontensorTest, DeeplyNestedTensorValueExceedsMaxRank) {
TensorInfoMap infomap;
ASSERT_TRUE(
TextFormat::ParseFromString("dtype: DT_INT32", &infomap["default"]));

PredictRequest req;
JsonPredictRequestFormat format;
std::string json_req = R"({"instances":)";
int depth = 300; // exceeds kMaxTensorRank (254)
json_req.append(depth, '[');
json_req.append("1");
json_req.append(depth, ']');
json_req.append("}");
auto status =
FillPredictRequestFromJson(json_req, getmap(infomap), &req, &format);
ASSERT_FALSE(status.ok());
EXPECT_EQ(status.code(), absl::StatusCode::kInvalidArgument);
}

TEST(JsontensorTest, MixedInputForFloatTensor) {
TensorInfoMap infomap;
ASSERT_TRUE(
Expand Down