Intel Optimization For Tensorflow vulnerabilities

CVE-2021-37676 [HIGH] CWE-824 Reference binding to nullptr in shape inference Reference binding to nullptr in shape inference ### Impact An attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.SparseFillEmptyRows`: ```python import tensorflow as tf tf.compat.v1.disable_v2_behavior() tf.raw_ops.SparseFillEmptyRows( indices = tf.constant([], shape=[0, 0], dtype=tf.int64), values = tf.constant([], shape=[0], dtype=tf.int64), dense_shape = tf.constant([], s

CVE-2021-37667 [HIGH] CWE-824 Reference binding to nullptr in unicode encoding Reference binding to nullptr in unicode encoding ### Impact An attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.UnicodeEncode`: ```python import tensorflow as tf from tensorflow.python.ops import gen_string_ops gen_string_ops.unicode_encode( input_values=[], input_splits=[], output_encoding='UTF-8', errors='ignore', replacement_char='a') ``` The [implementation](https://

CVE-2021-37655 [HIGH] CWE-125 Heap OOB in `ResourceScatterUpdate` Heap OOB in `ResourceScatterUpdate` ### Impact An attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to `tf.raw_ops.ResourceScatterUpdate`: ```python import tensorflow as tf v = tf.Variable([b'vvv']) tf.raw_ops.ResourceScatterUpdate( resource=v.handle, indices=[0], updates=['1', '2', '3', '4', '5']) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa

CVE-2022-23567 [MEDIUM] CWE-190 Integer overflows in Tensorflow Integer overflows in Tensorflow ### Impact The [implementations of `Sparse*Cwise*` ops](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc) are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based

CVE-2022-23568 [MEDIUM] CWE-190 Integer overflows in Tensorflow Integer overflows in Tensorflow ### Impact The [implementation of `AddManySparseToTensorsMap`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_tensors_map_ops.cc) is vulnerable to an integer overflow which results in a `CHECK`-fail when building new `TensorShape` objects (so, an assert failure based denial of service): ```python import tensorflow as tf import nu

CVE-2021-29518 [LOW] CWE-476 Session operations in eager mode lead to null pointer dereferences Session operations in eager mode lead to null pointer dereferences ### Impact In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference: ```python import tensorflow as tf tf.raw_ops.GetSessionTensor(handle=['\x12\x1a\x07'],dtype=4) ``` ```python import tensorflow as tf tf.raw_op

CVE-2023-25661 [MEDIUM] CWE-20 TensorFlow Denial of Service vulnerability TensorFlow Denial of Service vulnerability ### Impact A malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack. To minimize the bug, we built a simple single-layer TensorFlow model containing a Convolution3DTranspose layer, which works well with expected inputs and can be deployed in real-world systems. However, if we call the model with a malicious input wh

CVE-2022-23569 [MEDIUM] CWE-617 `CHECK`-fails when building invalid tensor shapes in Tensorflow `CHECK`-fails when building invalid tensor shapes in Tensorflow ### Impact Multiple operations in TensorFlow can be used to trigger a denial of service via `CHECK`-fails (i.e., assertion failures). This is similar to [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md) (CVE-2021-41197) and has similar fixes. ### Patches We have patched t

CVE-2022-21731 [HIGH] CWE-754 Type confusion leading to segfault in Tensorflow Type confusion leading to segfault in Tensorflow ### Impact The [implementation of shape inference for `ConcatV2`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059) can be used to trigger a denial of service attack via a segfault caused by a type confusion: ```python import tensorflow as tf @tf.function def test(): y = t

CVE-2022-21733 [MEDIUM] CWE-190 Memory exhaustion in Tensorflow Memory exhaustion in Tensorflow ### Impact The [implementation of `StringNGrams`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/string_ngrams_op.cc#L29-L161) can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow: ```python import tensorflow as tf tf.raw_ops.StringNGrams( data=['123456'], data_splits=[0,1], separator=

CVE-2022-21725 [MEDIUM] CWE-369 Division by zero in Tensorflow Division by zero in Tensorflow ### Impact The [estimator for the cost of some convolution operations](https://github.com/tensorflow/tensorflow/blob/ffa202a17ab7a4a10182b746d230ea66f021fe16/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L189-L198) can be made to execute a division by 0: ```python import tensorflow as tf @tf.function def test(): y=tf.raw_ops.AvgPoolGrad( orig_input_shape=[1,1,1,1], grad=[[[[1.0],[1.0],[1.

CVE-2020-15210 [HIGH] CWE-20 Segmentation fault in tensorflow-lite Segmentation fault in tensorflow-lite ### Impact If a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. ### Patches We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or

CVE-2022-23572 [HIGH] CWE-617 Crash when type cannot be specialized in Tensorflow Crash when type cannot be specialized in Tensorflow ### Impact Under certain scenarios, TensorFlow can fail to specialize a type during [shape inference](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174): ```cc void InferenceContext::PreInputInit( const OpDef& op_def, const std::vector& input_tensors, const std::vector& i

CVE-2022-21741 [HIGH] CWE-369 Division by zero in TFLite Division by zero in TFLite ### Impact An attacker can craft a TFLite model that would trigger a division by zero in [the implementation of depthwise convolutions](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/depthwise_conv.cc#L96). The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding tha

CVE-2022-21729 [HIGH] CWE-190 Overflow and uncaught divide by zero in Tensorflow Overflow and uncaught divide by zero in Tensorflow ### Impact The [implementation of `UnravelIndex`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/unravel_index_op.cc#L36-L135) is vulnerable to a division by zero caused by an integer overflow bug: ```python import tensorflow as tf tf.raw_ops.UnravelIndex(indices=-0x100000,dims=[0x100000,0x100000]) `

CVE-2022-21738 [HIGH] CWE-190 Integer overflow leading to crash in Tensorflow Integer overflow leading to crash in Tensorflow ### Impact The [implementation of `SparseCountSparseOutput`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/count_ops.cc#L168-L273) can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation: ```python import tensorflow as tf import numpy as np tf.raw_

CVE-2022-21732 [MEDIUM] CWE-400 Memory exhaustion in Tensorflow Memory exhaustion in Tensorflow ### Impact The [implementation of `ThreadPoolHandle`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135) can be used to trigger a denial of service attack by allocating too much memory: ```python import tensorflow as tf y = tf.raw_ops.ThreadPoolHandle(num_threads=0x60000000,display_name='

CVE-2022-23557 [HIGH] CWE-369 Division by zero in TFLite Division by zero in TFLite ### Impact An attacker can craft a TFLite model that would trigger a division by zero in [`BiasAndClamp` implementation](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75): ```cc inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size, const float* bias_data, int array_size, float* array_data) { // ... TFLITE_DCH

CVE-2020-15197 [MEDIUM] CWE-20 Denial of Service in Tensorflow Denial of Service in Tensorflow ### Impact The `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/co

CVE-2022-23571 [HIGH] CWE-617 Reachable Assertion in Tensorflow Reachable Assertion in Tensorflow ### Impact When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a `CHECK` assertion is invalidated based on user controlled arguments, if the tensors have an invalid `dtype` and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow processes. ### Patches We have patched the issue in GitHub commit [5b491cd5e41ad63735161cec9c2