Improper Input Validation Affecting tensorflow/tensorflow package, versions [,1.15.2)[2.0.0,2.0.1)


Severity

Recommended
0.0
high
0
10

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

Threat Intelligence

EPSS
0.69% (81st percentile)

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  • Snyk IDSNYK-UNMANAGED-TENSORFLOWTENSORFLOW-2333467
  • published12 Jan 2022
  • disclosed28 Jan 2020
  • creditUnknown

Introduced: 28 Jan 2020

CVE-2020-5215  (opens in a new tab)
CWE-20  (opens in a new tab)

How to fix?

Upgrade tensorflow/tensorflow to version 1.15.2, 2.0.1 or higher.

Overview

Affected versions of this package are vulnerable to Improper Input Validation. In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant("hello", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.

CVSS Scores

version 3.1