CVE-2021-29568

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger undefined behavior by binding to null pointer in tf.raw_ops.ParameterizedTruncatedNormal. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of shape. If shape argument is empty, then shape_tensor.flat<T>() is an empty array. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger undefined behavior by binding to null pointer in tf.raw_ops.ParameterizedTruncatedNormal. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of shape. If shape argument is empty, then shape_tensor.flat<T>() is an empty array. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Impact

An attacker can trigger undefined behavior by binding to null pointer in tf.raw_ops.ParameterizedTruncatedNormal:

import tensorflow as tf
    
shape = tf.constant([], shape=[0], dtype=tf.int32)
means = tf.constant((1), dtype=tf.float32)
stdevs = tf.constant((1), dtype=tf.float32)
minvals = tf.constant((1), dtype=tf.float32)
maxvals = tf.constant((1), dtype=tf.float32)
  
tf.raw_ops.ParameterizedTruncatedNormal(
  shape=shape, means=means, stdevs=stdevs, minvals=minvals, maxvals=maxvals)

This is because the implementation does not validate input arguments before accessing the first element of shape:

int32 num_batches = shape_tensor.flat<int32>()(0);

If shape argument is empty, then shape_tensor.flat<T>() is an empty array.

Patches

We have patched the issue in GitHub commit 5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

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 has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger undefined behavior by binding to null pointer in tf.raw_ops.ParameterizedTruncatedNormal. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of shape. If shape argument is empty, then shape_tensor.flat<T>() is an empty array. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger undefined behavior by binding to null pointer in tf.raw_ops.ParameterizedTruncatedNormal. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of shape. If shape argument is empty, then shape_tensor.flat<T>() is an empty array. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Impact

An attacker can trigger undefined behavior by binding to null pointer in tf.raw_ops.ParameterizedTruncatedNormal:

import tensorflow as tf
    
shape = tf.constant([], shape=[0], dtype=tf.int32)
means = tf.constant((1), dtype=tf.float32)
stdevs = tf.constant((1), dtype=tf.float32)
minvals = tf.constant((1), dtype=tf.float32)
maxvals = tf.constant((1), dtype=tf.float32)
  
tf.raw_ops.ParameterizedTruncatedNormal(
  shape=shape, means=means, stdevs=stdevs, minvals=minvals, maxvals=maxvals)

This is because the implementation does not validate input arguments before accessing the first element of shape:

int32 num_batches = shape_tensor.flat<int32>()(0);

If shape argument is empty, then shape_tensor.flat<T>() is an empty array.

Patches

We have patched the issue in GitHub commit 5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

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 has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.