Improper Check for Unusual or Exceptional Conditions 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
medium
0
10

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

Threat Intelligence

EPSS
0.09% (41st percentile)

Do your applications use this vulnerable package?

In a few clicks we can analyze your entire application and see what components are vulnerable in your application, and suggest you quick fixes.

Test your applications
  • Snyk IDSNYK-UNMANAGED-TENSORFLOWTENSORFLOW-2333462
  • published12 Jan 2022
  • disclosed14 May 2021
  • creditUnknown

Introduced: 14 May 2021

CVE-2021-29533  (opens in a new tab)
CWE-754  (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 Improper Check for Unusual or Exceptional Conditions. TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a CHECK failure by passing an empty image to tf.raw_ops.DrawBoundingBoxes. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses CHECK_* assertions instead of OP_REQUIRES to validate user controlled inputs. Whereas OP_REQUIRES allows returning an error condition back to the user, the CHECK_* macros result in a crash if the condition is false, similar to assert. In this case, height is 0 from the images input. This results in max_box_row_clamp being negative and the assertion being falsified, followed by aborting program execution. 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