TensorFlow TFLite model FPE (filter_input_channel<1) fixed in 2.12
CVE-2023-27579 Published on March 25, 2023

TensorFlow has Floating Point Exception in TFLite in conv kernel
TensorFlow is an end-to-end open source platform for machine learning. Constructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE. This issue has been patched in version 2.12. TensorFlow will also cherrypick the fix commit on TensorFlow 2.11.1.

NVD

Vulnerability Analysis

CVE-2023-27579 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-2023-27579

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Affected Versions

tensorflow Version < 2.11.1 is affected by CVE-2023-27579

Exploit Probability

EPSS
0.18%
Percentile
39.84%

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.