Out-of-bounds Write Affecting tensorflow/tensorflow package, versions [,2.1.4)[2.2.0,2.2.3)[2.3.0,2.3.3)[2.4.0,2.4.2)


Severity

Recommended
0.0
high
0
10

CVSS assessment made by Snyk's Security Team. Learn more

Threat Intelligence

EPSS
0.04% (6th percentile)

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  • Snyk IDSNYK-UNMANAGED-TENSORFLOWTENSORFLOW-2333359
  • published12 Jan 2022
  • disclosed14 May 2021
  • creditUnknown

Introduced: 14 May 2021

CVE-2021-29566  (opens in a new tab)
CWE-787  (opens in a new tab)

How to fix?

Upgrade tensorflow/tensorflow to version 2.1.4, 2.2.3, 2.3.3, 2.4.2 or higher.

Overview

Affected versions of this package are vulnerable to Out-of-bounds Write. TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to tf.raw_ops.Dilation2DBackpropInput. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for h_out and w_out are guaranteed to be in range for out_backprop (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating h_in_max/w_in_max and in_backprop. 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.

CVSS Scores

version 3.1