Vulnerabilities > CVE-2021-41197 - Integer Overflow or Wraparound vulnerability in Google Tensorflow

047910
CVSS 2.1 - LOW
Attack vector
LOCAL
Attack complexity
LOW
Privileges required
NONE
Confidentiality impact
NONE
Integrity impact
NONE
Availability impact
PARTIAL
local
low complexity
google
CWE-190
NVD
Published: 2021-11-05
Updated: 2021-11-09

Summary

TensorFlow is an open source platform for machine learning. In affected versions TensorFlow allows tensor to have a large number of dimensions and each dimension can be as large as desired. However, the total number of elements in a tensor must fit within an `int64_t`. If an overflow occurs, `MultiplyWithoutOverflow` would return a negative result. In the majority of TensorFlow codebase this then results in a `CHECK`-failure. Newer constructs exist which return a `Status` instead of crashing the binary. This is similar to CVE-2021-29584. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Vulnerable Configurations

Part Description Count
Application
Google
398

Common Weakness Enumeration (CWE)

Common Attack Pattern Enumeration and Classification (CAPEC)

  • Forced Integer Overflow
    This attack forces an integer variable to go out of range. The integer variable is often used as an offset such as size of memory allocation or similarly. The attacker would typically control the value of such variable and try to get it out of range. For instance the integer in question is incremented past the maximum possible value, it may wrap to become a very small, or negative number, therefore providing a very incorrect value which can lead to unexpected behavior. At worst the attacker can execute arbitrary code.

References