NULL Pointer Dereference Affecting tensorflow/tensorflow package, versions [2.3.0,2.3.4)[2.4.0,2.4.3)


Severity

Recommended
0.0
high
0
10

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

Threat Intelligence

EPSS
0.09% (41st percentile)

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  • Snyk IDSNYK-UNMANAGED-TENSORFLOWTENSORFLOW-2333389
  • published12 Jan 2022
  • disclosed12 Aug 2021
  • creditUnknown

Introduced: 12 Aug 2021

CVE-2021-37648  (opens in a new tab)
CWE-476  (opens in a new tab)

How to fix?

Upgrade tensorflow/tensorflow to version 2.3.4, 2.4.3 or higher.

Overview

Affected versions of this package are vulnerable to NULL Pointer Dereference. TensorFlow is an end-to-end open source platform for machine learning. In affected versions the code for tf.raw_ops.SaveV2 does not properly validate the inputs and an attacker can trigger a null pointer dereference. The implementation uses ValidateInputs to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above. However, the validation uses OP_REQUIRES which translates to setting the Status object of the current OpKernelContext to an error status, followed by an empty return statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in Compute that follows the call to ValidateInputs. This is equivalent to lacking the validation. We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

CVSS Scores

version 3.1