8.8

CVE-2022-21727

Exploit

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.

Data is provided by the National Vulnerability Database (NVD)
Google ≫ Tensorflow Version <= 2.5.2
Google ≫ Tensorflow Version >= 2.6.0 <= 2.6.2
Google ≫ Tensorflow Version2.7.0
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
EPSS Metriken
Type Source Score Percentile
EPSS FIRST.org 0.33% 0.552
CVSS Metriken
Source Base Score Exploit Score Impact Score Vector string
nvd@nist.gov 8.8 2.8 5.9
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
nvd@nist.gov 6.5 8 6.4
AV:N/AC:L/Au:S/C:P/I:P/A:P
security-advisories@github.com 7.6 2.8 4.7
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
CWE-190 Integer Overflow or Wraparound

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 occurs when an integer value is incremented to a value that is too large to store in the associated representation. When this occurs, the value may become a very small or negative number.