Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. 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 2022-02-03 11:15:08
Updated 2022-02-08 20:14:45
Source GitHub, Inc.
View at NVD,   CVE.org
Vulnerability category: Overflow

Exploit prediction scoring system (EPSS) score for CVE-2022-21727

0.36%
Probability of exploitation activity in the next 30 days EPSS Score History
~ 72 %
Percentile, the proportion of vulnerabilities that are scored at or less

CVSS scores for CVE-2022-21727

Base Score Base Severity CVSS Vector Exploitability Score Impact Score Score Source First Seen
6.5
MEDIUM AV:N/AC:L/Au:S/C:P/I:P/A:P
8.0
6.4
NIST
8.8
HIGH CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
2.8
5.9
NIST
7.6
HIGH CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
2.8
4.7
GitHub, Inc.

CWE ids for CVE-2022-21727

  • The product performs a calculation that can produce an integer overflow or wraparound, when the logic assumes that the resulting value will always be larger than the original value. This can introduce other weaknesses when the calculation is used for resource management or execution control.
    Assigned by: nvd@nist.gov (Primary)

References for CVE-2022-21727

Products affected by CVE-2022-21727

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