Vulnerabilities > CVE-2022-35940 - Integer Overflow or Wraparound vulnerability in Google Tensorflow

047910
CVSS 7.5 - HIGH
Attack vector
NETWORK
Attack complexity
LOW
Privileges required
NONE
Confidentiality impact
NONE
Integrity impact
NONE
Availability impact
HIGH
network
low complexity
google
CWE-190
NVD
Published: 2022-09-16
Updated: 2022-09-20

Summary

TensorFlow is an open source platform for machine learning. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Vulnerable Configurations

Part Description Count
Application
Google
17

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