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### Impact If [`tf.raw_ops.TensorListResize`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/list_kernels.cc) is given a nonscalar value for input `size`, it results `CHECK` fail which can be used to trigger a denial of service attack. ```python import numpy as np import tensorflow as tf a = data_structures.tf_tensor_list_new(elements = tf.constant(value=[3, 4, 5])) b = np.zeros([0, 2, 3, 3]) tf.raw_ops.TensorListResize(input_handle=a, size=b) ``` ### Patches We have patched the issue in GitHub commit [888e34b49009a4e734c27ab0c43b0b5102682c56](https://github.com/tensorflow/tensorflow/commit/888e34b49009a4e734c27ab0c43b0b5102682c56). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for mor...

### Impact If [`tf.raw_ops.TensorListConcat`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/list_kernels.h) is given `element_shape=[]`, it results segmentation fault which can be used to trigger a denial of service attack. ```python import tensorflow as tf tf.raw_ops.TensorListConcat( input_handle=tf.data.experimental.to_variant(tf.data.Dataset.from_tensor_slices([1, 2, 3])), element_dtype=tf.dtypes.float32, element_shape=[] ) ``` ### Patches We have patched the issue in GitHub commit [fc33f3dc4c14051a83eec6535b608abe1d355fde](https://github.com/tensorflow/tensorflow/commit/fc33f3dc4c14051a83eec6535b608abe1d355fde). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more inf...

### Impact If [`BCast::ToShape`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/util/bcast.h) is given input larger than an `int32`, it will crash, despite being supposed to handle up to an `int64`. An example can be seen in [`tf.experimental.numpy.outer`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/util/bcast.h) by passing in large input to the input `b`. ```python import tensorflow as tf value = tf.constant(shape=[2, 1024, 1024, 1024], value=False) tf.experimental.numpy.outer(a=6,b=value) ``` ### Patches We have patched the issue in GitHub commit [8310bf8dd188ff780e7fc53245058215a05bdbe5](https://github.com/tensorflow/tensorflow/commit/8310bf8dd188ff780e7fc53245058215a05bdbe5). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://gi...

### Impact If a list of quantized tensors is assigned to an attribute, the pywrap code fails to parse the tensor and returns a `nullptr`, which is not caught. An example can be seen in [`tf.compat.v1.extract_volume_patches`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/image/generate_box_proposals_op.cu.cc) by passing in quantized tensors as input `ksizes`. ```python import numpy as np import tensorflow as tf a_input = np.array([1, -1], dtype= np.int32) a_ksizes = a_strides = tf.constant(dtype=tf.dtypes.qint16, value=[[1, 4], [5, 2]]) tf.compat.v1.extract_volume_patches(input=a_input,ksizes=a_ksizes,strides=a_strides,padding='VALID') ``` ### Patches We have patched the issue in GitHub commit [e9e95553e5411834d215e6770c81a83a3d0866ce](https://github.com/tensorflow/tensorflow/commit/e9e95553e5411834d215e6770c81a83a3d0866ce). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2....

### Impact When running on GPU, [`tf.image.generate_bounding_box_proposals`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/image/generate_box_proposals_op.cu.cc) receives a `scores` input that must be of rank 4 but is not checked. ```python import tensorflow as tf a = tf.constant(value=[[1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0]]) b = tf.constant(value=[1]) tf.image.generate_bounding_box_proposals(scores=a,bbox_deltas=a,image_info=a,anchors=a,pre_nms_topn=b) ``` ### Patches We have patched the issue in GitHub commit [cf35502463a88ca7185a99daa7031df60b3c1c98](https://github.com/tensorflow/tensorflow/commit/cf35502463a88ca7185a99daa7031df60b3c1c98). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/...

### Impact [`tf.keras.losses.poisson`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/keras/losses.py) receives a `y_pred` and `y_true` that are passed through `functor::mul` in [`BinaryOp`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/cwise_ops_common.h). If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. ```python import numpy as np import tensorflow as tf true_value = tf.reshape(shape=[1, 2500000000], tensor = tf.zeros(dtype=tf.bool, shape=[50000, 50000])) pred_value = np.array([[[-2]], [[8]]], dtype = np.float64) tf.keras.losses.poisson(y_true=true_value,y_pred=pred_value) ``` ### Patches We have patched the issue in GitHub commit [c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c](https://github.com/tensorflow/tensorflow/commit/c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorF...

### Impact When [`tf.raw_ops.ImageProjectiveTransformV2`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/image/image_ops.cc) is given a large output shape, it overflows. ```python import tensorflow as tf interpolation = "BILINEAR" fill_mode = "REFLECT" images = tf.constant(0.184634328, shape=[2,5,8,3], dtype=tf.float32) transforms = tf.constant(0.378575385, shape=[2,8], dtype=tf.float32) output_shape = tf.constant([1879048192,1879048192], shape=[2], dtype=tf.int32) tf.raw_ops.ImageProjectiveTransformV2(images=images, transforms=transforms, output_shape=output_shape, interpolation=interpolation, fill_mode=fill_mode) ``` ### Patches We have patched the issue in GitHub commit [8faa6ea692985dbe6ce10e1a3168e0bd60a723ba](https://github.com/tensorflow/tensorflow/commit/8faa6ea692985dbe6ce10e1a3168e0bd60a723ba). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also a...

### Impact When [`tf.raw_ops.FusedResizeAndPadConv2D`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/conv_ops_fused_image_transform.cc) is given a large tensor shape, it overflows. ```python import tensorflow as tf mode = "REFLECT" strides = [1, 1, 1, 1] padding = "SAME" resize_align_corners = False input = tf.constant(147, shape=[3,3,1,1], dtype=tf.float16) size = tf.constant([1879048192,1879048192], shape=[2], dtype=tf.int32) paddings = tf.constant([3,4], shape=[2], dtype=tf.int32) filter = tf.constant(123, shape=[1,3,4,1], dtype=tf.float16) tf.raw_ops.FusedResizeAndPadConv2D(input=input, size=size, paddings=paddings, filter=filter, mode=mode, strides=strides, padding=padding, resize_align_corners=resize_align_corners) ``` ### Patches We have patched the issue in GitHub commit [d66e1d568275e6a2947de97dca7a102a211e01ce](https://github.com/tensorflow/tensorflow/commit/d66e1d568275e6a2947de97dca7a102a211e01ce). The fix will be included in TensorFlow 2.1...

### Impact If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error: ```python np.ones((0, 2**31, 2**31)) ``` An example of a proof of concept: ```python import numpy as np import tensorflow as tf input_val = tf.constant([1]) shape_val = np.array([i for i in range(21)]) tf.broadcast_to(input=input_val,shape=shape_val) ``` The return value of `PyArray_SimpleNewFromData`, which returns null on such shapes, is not checked. ### Patches We have patched the issue in GitHub commit [2b56169c16e375c521a3bc8ea658811cc0793784](https://github.com/tensorflow/tensorflow/commit/2b56169c16e375c521a3bc8ea658811cc0793784). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/...

### Impact [`tf.raw_ops.DynamicStitch`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/dynamic_stitch_op.cc) specifies input sizes when it is [registered](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/data_flow_ops.cc). ```cpp REGISTER_OP("DynamicStitch") .Input("indices: N * int32") .Input("data: N * T") .Output("merged: T") .Attr("N : int >= 1") .Attr("T : type") .SetShapeFn(DynamicStitchShapeFunction); ``` When it receives a differing number of inputs, such as when it is called with an `indices` size 1 and a `data` size 2, it will crash. ```python import tensorflow as tf # indices = 1*[tf.random.uniform([1,2], dtype=tf.dtypes.int32, maxval=100)] indices = [tf.constant([[0, 1]]),] # data = 2*[tf.random.uniform([1,2], dtype=tf.dtypes.float32, maxval=100)] data = [tf.constant([[5, 6]]), tf.constant([[7, 8]])] tf.raw_ops.DynamicStitch( indices=indices, data=data) ``` ### Patches We have patch...