Vulnerability Monitor

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CVE-2021-37659

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations). The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/cwise_ops_common.h#L264) assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads and undefined behavior due to binding to nullptr. We have patched the issue in GitHub commit 93f428fd1768df147171ed674fee1fc5ab8309ec. 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.

Published

2021-08-12T21:15:08.763

Last Modified

2024-11-21T06:15:38.123

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 7.3 (HIGH)

CVSSv2 Vector

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

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

3.9

Impact Score

6.4

Weaknesses
  • Type: Primary
    CWE-125
    CWE-476
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 2.3.4 Yes
Application google tensorflow < 2.4.3 Yes
Application google tensorflow 2.5.0 Yes
Application google tensorflow 2.6.0 Yes
Application google tensorflow 2.6.0 Yes
Application google tensorflow 2.6.0 Yes
References