Vulnerability Monitor

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CVE-2021-29522

TensorFlow is an end-to-end open source platform for machine learning. The `tf.raw_ops.Conv3DBackprop*` operations fail to validate that the input tensors are not empty. In turn, this would result in a division by 0. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) does not check that the divisor used in computing the shard size is not zero. Thus, if attacker controls the input sizes, they can trigger a denial of service via a division by zero error. 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.

Published

2021-05-14T20:15:11.617

Last Modified

2024-11-21T06:01:18.193

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 2.5 (LOW)

CVSSv2 Vector

AV:L/AC:L/Au:N/C:N/I:N/A:P

  • Access Vector: LOCAL
  • Access Complexity: LOW
  • Authentication: NONE
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: PARTIAL
Exploitability Score

3.9

Impact Score

2.9

Weaknesses
  • Type: Primary
    CWE-369
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 2.1.4 Yes
Application google tensorflow < 2.2.3 Yes
Application google tensorflow < 2.3.3 Yes
Application google tensorflow < 2.4.2 Yes
References