Vulnerabilities > CVE-2022-41887 - Incorrect Calculation of Buffer Size 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-131
NVD
Published: 2022-11-18
Updated: 2022-11-22

Summary

TensorFlow is an open source platform for machine learning. `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.

Vulnerable Configurations

Part Description Count
Application
Google
7

Common Weakness Enumeration (CWE)

Common Attack Pattern Enumeration and Classification (CAPEC)

  • Overflow Buffers
    Buffer Overflow attacks target improper or missing bounds checking on buffer operations, typically triggered by input injected by an attacker. As a consequence, an attacker is able to write past the boundaries of allocated buffer regions in memory, causing a program crash or potentially redirection of execution as per the attackers' choice.
  • Buffer Overflow via Parameter Expansion
    In this attack, the target software is given input that the attacker knows will be modified and expanded in size during processing. This attack relies on the target software failing to anticipate that the expanded data may exceed some internal limit, thereby creating a buffer overflow.

References