Vulnerability Monitor

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CVE-2022-21728


Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.


Published

2022-02-03T11:15:08.020

Last Modified

2025-05-05T17:17:48.900

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 8.1 (HIGH)

CVSSv2 Vector

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

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

8.0

Impact Score

4.9

Weaknesses
  • Type: Primary
    CWE-125
  • Type: Secondary
    CWE-125

Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow ≤ 2.5.2 Yes
Application google tensorflow ≤ 2.6.2 Yes
Application google tensorflow 2.7.0 Yes

References