TensorFlow OOB Read: indices mismatch pre-2.12.0/2.11.1
CVE-2023-25659 Published on March 25, 2023

TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch
TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the parameter `indices` for `DynamicStitch` does not match the shape of the parameter `data`, it can trigger an stack OOB read. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.

NVD

Vulnerability Analysis

CVE-2023-25659 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

Out-of-bounds Read

The software reads data past the end, or before the beginning, of the intended buffer. Typically, this can allow attackers to read sensitive information from other memory locations or cause a crash. A crash can occur when the code reads a variable amount of data and assumes that a sentinel exists to stop the read operation, such as a NUL in a string. The expected sentinel might not be located in the out-of-bounds memory, causing excessive data to be read, leading to a segmentation fault or a buffer overflow. The software may modify an index or perform pointer arithmetic that references a memory location that is outside of the boundaries of the buffer. A subsequent read operation then produces undefined or unexpected results.


Products Associated with CVE-2023-25659

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Google Tensorflow
 

Affected Versions

tensorflow Version < 2.11.1 is affected by CVE-2023-25659

Exploit Probability

EPSS
0.18%
Percentile
39.63%

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.