CVE-2023-25801

TensorFlow is an open source machine learning platform. Prior to versions 2.12.0 and 2.11.1, nn_ops.fractional_avg_pool_v2 and nn_ops.fractional_max_pool_v2 require the first and fourth elements of their parameter pooling_ratio to be equal to 1.0, as pooling on batch and channel dimensions is not supported. A fix is included in TensorFlow 2.12.0 and 2.11.1.

Impact

nn_ops.fractional_avg_pool_v2 and nn_ops.fractional_max_pool_v2 require the first and fourth elements of their parameter pooling_ratio to be equal to 1.0, as pooling on batch and channel dimensions is not supported.

import tensorflow as tf
import os
import numpy as np
from tensorflow.python.ops import nn_ops
try:
  arg_0_tensor = tf.random.uniform([3, 30, 50, 3], dtype=tf.float64)
  arg_0 = tf.identity(arg_0_tensor)
  arg_1_0 = 2
  arg_1_1 = 3
  arg_1_2 = 1
  arg_1_3 = 1
  arg_1 = [arg_1_0,arg_1_1,arg_1_2,arg_1_3,]
  arg_2 = True
  arg_3 = True
  seed = 341261001
  out = nn_ops.fractional_avg_pool_v2(arg_0,arg_1,arg_2,arg_3,seed=seed,)
except Exception as e:
  print("Error:"+str(e))

Patches

We have patched the issue in GitHub commit ee50d1e00f81f62a4517453f721c634bbb478307.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by dmc1778, of [email protected].

Impact

nn_ops.fractional_avg_pool_v2 and nn_ops.fractional_max_pool_v2 require the first and fourth elements of their parameter pooling_ratio to be equal to 1.0, as pooling on batch and channel dimensions is not supported.

import tensorflow as tf
import os
import numpy as np
from tensorflow.python.ops import nn_ops
try:
  arg_0_tensor = tf.random.uniform([3, 30, 50, 3], dtype=tf.float64)
  arg_0 = tf.identity(arg_0_tensor)
  arg_1_0 = 2
  arg_1_1 = 3
  arg_1_2 = 1
  arg_1_3 = 1
  arg_1 = [arg_1_0,arg_1_1,arg_1_2,arg_1_3,]
  arg_2 = True
  arg_3 = True
  seed = 341261001
  out = nn_ops.fractional_avg_pool_v2(arg_0,arg_1,arg_2,arg_3,seed=seed,)
except Exception as e:
  print("Error:"+str(e))

Patches

We have patched the issue in GitHub commit ee50d1e00f81f62a4517453f721c634bbb478307.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by dmc1778, of [email protected].

Impact

nn_ops.fractional_avg_pool_v2 and nn_ops.fractional_max_pool_v2 require the first and fourth elements of their parameter pooling_ratio to be equal to 1.0, as pooling on batch and channel dimensions is not supported.

import tensorflow as tf
import os
import numpy as np
from tensorflow.python.ops import nn_ops
try:
  arg_0_tensor = tf.random.uniform([3, 30, 50, 3], dtype=tf.float64)
  arg_0 = tf.identity(arg_0_tensor)
  arg_1_0 = 2
  arg_1_1 = 3
  arg_1_2 = 1
  arg_1_3 = 1
  arg_1 = [arg_1_0,arg_1_1,arg_1_2,arg_1_3,]
  arg_2 = True
  arg_3 = True
  seed = 341261001
  out = nn_ops.fractional_avg_pool_v2(arg_0,arg_1,arg_2,arg_3,seed=seed,)
except Exception as e:
  print("Error:"+str(e))

Patches

We have patched the issue in GitHub commit ee50d1e00f81f62a4517453f721c634bbb478307.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by dmc1778, of [email protected].

Impact

nn_ops.fractional_avg_pool_v2 and nn_ops.fractional_max_pool_v2 require the first and fourth elements of their parameter pooling_ratio to be equal to 1.0, as pooling on batch and channel dimensions is not supported.

import tensorflow as tf
import os
import numpy as np
from tensorflow.python.ops import nn_ops
try:
  arg_0_tensor = tf.random.uniform([3, 30, 50, 3], dtype=tf.float64)
  arg_0 = tf.identity(arg_0_tensor)
  arg_1_0 = 2
  arg_1_1 = 3
  arg_1_2 = 1
  arg_1_3 = 1
  arg_1 = [arg_1_0,arg_1_1,arg_1_2,arg_1_3,]
  arg_2 = True
  arg_3 = True
  seed = 341261001
  out = nn_ops.fractional_avg_pool_v2(arg_0,arg_1,arg_2,arg_3,seed=seed,)
except Exception as e:
  print("Error:"+str(e))

Patches

We have patched the issue in GitHub commit ee50d1e00f81f62a4517453f721c634bbb478307.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by dmc1778, of [email protected].

TensorFlow is an open source machine learning platform. Prior to versions 2.12.0 and 2.11.1, nn_ops.fractional_avg_pool_v2 and nn_ops.fractional_max_pool_v2 require the first and fourth elements of their parameter pooling_ratio to be equal to 1.0, as pooling on batch and channel dimensions is not supported. A fix is included in TensorFlow 2.12.0 and 2.11.1.