TensorFlow XLA Segfault via tf.raw_ops.Bincount Weights Param - Pre-2.12/2.11.1
CVE-2023-25675 Published on March 25, 2023

TensorFlow has Segfault in Bincount with XLA
TensorFlow is an open source machine learning platform. When running versions prior to 2.12.0 and 2.11.1 with XLA, `tf.raw_ops.Bincount` segfaults when given a parameter `weights` that is neither the same shape as parameter `arr` nor a length-0 tensor. A fix is included in TensorFlow 2.12.0 and 2.11.1.

NVD

Vulnerability Analysis

CVE-2023-25675 can be exploited with network access, and does not require authorization privileges or user interaction. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to have no impact on confidentiality and integrity, and a high impact on availability.

Attack Vector:
NETWORK
Attack Complexity:
LOW
Privileges Required:
NONE
User Interaction:
NONE
Scope:
UNCHANGED
Confidentiality Impact:
NONE
Integrity Impact:
NONE
Availability Impact:
HIGH

Weakness Type

Incorrect Comparison

The software compares two entities in a security-relevant context, but the comparison is incorrect, which may lead to resultant weaknesses.


Products Associated with CVE-2023-25675

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Google Tensorflow
 

Affected Versions

tensorflow Version < 2.11.1 is affected by CVE-2023-25675

Exploit Probability

EPSS
0.18%
Percentile
39.89%

EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.