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Prevent format string vulnerability in
tf.strings.as_string.
The `printf` format specifier only allows `#`, `0`, `-`, `+` and space as flag characters. Others are interpreted as width/precision/length modifier or conversion specifiers. If a character does not fit into any of these sets `printf` just displays it. Also add a test suite for `tf.strings.as_string`. Also fix the issue where the flag character was used only if width was specified. PiperOrigin-RevId: 332553548 Change-Id: Ie57cf2a7c14d1a36097642794c14329db669bbba
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,245 @@ | ||
| /* Copyright 2020 The TensorFlow Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. | ||
| ==============================================================================*/ | ||
|
|
||
| #include "tensorflow/core/framework/fake_input.h" | ||
| #include "tensorflow/core/framework/node_def_builder.h" | ||
| #include "tensorflow/core/framework/tensor.h" | ||
| #include "tensorflow/core/framework/tensor_testutil.h" | ||
| #include "tensorflow/core/framework/types.h" | ||
| #include "tensorflow/core/kernels/ops_testutil.h" | ||
| #include "tensorflow/core/kernels/ops_util.h" | ||
| #include "tensorflow/core/lib/core/status_test_util.h" | ||
|
|
||
| namespace tensorflow { | ||
| namespace { | ||
|
|
||
| class AsStringGraphTest : public OpsTestBase { | ||
| protected: | ||
| Status Init(DataType input_type, const string& fill = "", int width = -1, | ||
| int precision = -1, bool scientific = false, | ||
| bool shortest = false) { | ||
| TF_CHECK_OK(NodeDefBuilder("op", "AsString") | ||
| .Input(FakeInput(input_type)) | ||
| .Attr("fill", fill) | ||
| .Attr("precision", precision) | ||
| .Attr("scientific", scientific) | ||
| .Attr("shortest", shortest) | ||
| .Attr("width", width) | ||
| .Finalize(node_def())); | ||
| return InitOp(); | ||
| } | ||
| }; | ||
|
|
||
| TEST_F(AsStringGraphTest, Int8) { | ||
| TF_ASSERT_OK(Init(DT_INT8)); | ||
|
|
||
| AddInputFromArray<int8>(TensorShape({3}), {-42, 0, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({3})); | ||
| test::FillValues<tstring>(&expected, {"-42", "0", "42"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, Int64) { | ||
| TF_ASSERT_OK(Init(DT_INT64)); | ||
|
|
||
| AddInputFromArray<int64>(TensorShape({3}), {-42, 0, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({3})); | ||
| test::FillValues<tstring>(&expected, {"-42", "0", "42"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FloatDefault) { | ||
| TF_ASSERT_OK(Init(DT_FLOAT)); | ||
|
|
||
| AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({4})); | ||
| test::FillValues<tstring>( | ||
| &expected, {"-42.000000", "0.000000", "3.141590", "42.000000"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FloatScientific) { | ||
| TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/-1, /*precision=*/-1, | ||
| /*scientific=*/true)); | ||
|
|
||
| AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({4})); | ||
| test::FillValues<tstring>(&expected, {"-4.200000e+01", "0.000000e+00", | ||
| "3.141590e+00", "4.200000e+01"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FloatShortest) { | ||
| TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/-1, /*precision=*/-1, | ||
| /*scientific=*/false, /*shortest=*/true)); | ||
|
|
||
| AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({4})); | ||
| test::FillValues<tstring>(&expected, {"-42", "0", "3.14159", "42"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FloatPrecisionOnly) { | ||
| TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/-1, /*precision=*/2)); | ||
|
|
||
| AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({4})); | ||
| test::FillValues<tstring>(&expected, {"-42.00", "0.00", "3.14", "42.00"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FloatWidthOnly) { | ||
| TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/5)); | ||
|
|
||
| AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({4})); | ||
| test::FillValues<tstring>( | ||
| &expected, {"-42.000000", "0.000000", "3.141590", "42.000000"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, Float_5_2_Format) { | ||
| TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/5, /*precision=*/2)); | ||
|
|
||
| AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({4})); | ||
| test::FillValues<tstring>(&expected, {"-42.00", " 0.00", " 3.14", "42.00"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, Complex) { | ||
| TF_ASSERT_OK(Init(DT_COMPLEX64, /*fill=*/"", /*width=*/5, /*precision=*/2)); | ||
|
|
||
| AddInputFromArray<complex64>(TensorShape({3}), {{-4, 2}, {0}, {3.14159, -1}}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({3})); | ||
| test::FillValues<tstring>( | ||
| &expected, {"(-4.00, 2.00)", "( 0.00, 0.00)", "( 3.14,-1.00)"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, Bool) { | ||
| TF_ASSERT_OK(Init(DT_BOOL)); | ||
|
|
||
| AddInputFromArray<bool>(TensorShape({2}), {true, false}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({2})); | ||
| test::FillValues<tstring>(&expected, {"true", "false"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, String) { | ||
| Status s = Init(DT_STRING); | ||
| ASSERT_EQ(error::INVALID_ARGUMENT, s.code()); | ||
| ASSERT_TRUE(absl::StrContains( | ||
| s.error_message(), | ||
| "Value for attr 'T' of string is not in the list of allowed values")); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, OnlyOneOfScientificAndShortest) { | ||
| Status s = Init(DT_FLOAT, /*fill=*/"", /*width=*/-1, /*precision=*/-1, | ||
| /*scientific=*/true, /*shortest=*/true); | ||
| ASSERT_EQ(error::INVALID_ARGUMENT, s.code()); | ||
| ASSERT_TRUE( | ||
| absl::StrContains(s.error_message(), | ||
| "Cannot select both scientific and shortest notation")); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, NoShortestForNonFloat) { | ||
| Status s = Init(DT_INT32, /*fill=*/"", /*width=*/-1, /*precision=*/-1, | ||
| /*scientific=*/false, /*shortest=*/true); | ||
| ASSERT_EQ(error::INVALID_ARGUMENT, s.code()); | ||
| ASSERT_TRUE(absl::StrContains( | ||
| s.error_message(), | ||
| "scientific and shortest format not supported for datatype")); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, NoScientificForNonFloat) { | ||
| Status s = Init(DT_INT32, /*fill=*/"", /*width=*/-1, /*precision=*/-1, | ||
| /*scientific=*/true); | ||
| ASSERT_EQ(error::INVALID_ARGUMENT, s.code()); | ||
| ASSERT_TRUE(absl::StrContains( | ||
| s.error_message(), | ||
| "scientific and shortest format not supported for datatype")); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, NoPrecisionForNonFloat) { | ||
| Status s = Init(DT_INT32, /*fill=*/"", /*width=*/-1, /*precision=*/5); | ||
| ASSERT_EQ(error::INVALID_ARGUMENT, s.code()); | ||
| ASSERT_TRUE(absl::StrContains(s.error_message(), | ||
| "precision not supported for datatype")); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, LongFill) { | ||
| Status s = Init(DT_INT32, /*fill=*/"asdf"); | ||
| ASSERT_EQ(error::INVALID_ARGUMENT, s.code()); | ||
| ASSERT_TRUE(absl::StrContains(s.error_message(), | ||
| "Fill string must be one or fewer characters")); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FillWithZero) { | ||
| TF_ASSERT_OK(Init(DT_INT64, /*fill=*/"0", /*width=*/4)); | ||
|
|
||
| AddInputFromArray<int64>(TensorShape({3}), {-42, 0, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({3})); | ||
| test::FillValues<tstring>(&expected, {"-042", "0000", "0042"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FillWithSpace) { | ||
| TF_ASSERT_OK(Init(DT_INT64, /*fill=*/" ", /*width=*/4)); | ||
|
|
||
| AddInputFromArray<int64>(TensorShape({3}), {-42, 0, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({3})); | ||
| test::FillValues<tstring>(&expected, {" -42", " 0", " 42"}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FillWithChar1) { | ||
| TF_ASSERT_OK(Init(DT_INT64, /*fill=*/"-", /*width=*/4)); | ||
|
|
||
| AddInputFromArray<int64>(TensorShape({3}), {-42, 0, 42}); | ||
| TF_ASSERT_OK(RunOpKernel()); | ||
| Tensor expected(allocator(), DT_STRING, TensorShape({3})); | ||
| test::FillValues<tstring>(&expected, {"-42 ", "0 ", "42 "}); | ||
| test::ExpectTensorEqual<tstring>(expected, *GetOutput(0)); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FillWithChar3) { | ||
| Status s = Init(DT_INT32, /*fill=*/"s"); | ||
| ASSERT_EQ(error::INVALID_ARGUMENT, s.code()); | ||
| ASSERT_TRUE( | ||
| absl::StrContains(s.error_message(), "Fill argument not supported")); | ||
| } | ||
|
|
||
| TEST_F(AsStringGraphTest, FillWithChar4) { | ||
| Status s = Init(DT_INT32, /*fill=*/"n"); | ||
| ASSERT_EQ(error::INVALID_ARGUMENT, s.code()); | ||
| ASSERT_TRUE( | ||
| absl::StrContains(s.error_message(), "Fill argument not supported")); | ||
| } | ||
|
|
||
| } // end namespace | ||
| } // end namespace tensorflow |