DoS via Invalid Size in tf.raw_ops.TensorListResize (TensorFlow <=2.11)
CVE-2022-41893 Published on November 18, 2022

`CHECK_EQ` fail in `tf.raw_ops.TensorListResize` in Tensorflow
TensorFlow is an open source platform for machine learning. If `tf.raw_ops.TensorListResize` is given a nonscalar value for input `size`, it results `CHECK` fail which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 888e34b49009a4e734c27ab0c43b0b5102682c56. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

Github Repository NVD

Vulnerability Analysis

CVE-2022-41893 can be exploited with network access, requires user interaction and a small amount of user privileges. This vulnerability is consided to have a high level of attack complexity. Public availability of a proof of concept (POC) exploit exists for CVE-2022-41893. 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:
HIGH
Privileges Required:
LOW
User Interaction:
REQUIRED
Scope:
UNCHANGED
Confidentiality Impact:
NONE
Integrity Impact:
NONE
Availability Impact:
HIGH

Weakness Type

What is an assertion failure Vulnerability?

The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary.

CVE-2022-41893 has been classified to as an assertion failure vulnerability or weakness.


Products Associated with CVE-2022-41893

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Affected Versions

tensorflow:

Vulnerable Packages

The following package name and versions may be associated with CVE-2022-41893

Package Manager Vulnerable Package Versions Fixed In
pip tensorflow < 2.8.4 2.8.4
pip tensorflow >= 2.9.0, < 2.9.3 2.9.3
pip tensorflow >= 2.10.0, < 2.10.1 2.10.1
pip tensorflow-cpu < 2.8.4 2.8.4
pip tensorflow-gpu < 2.8.4 2.8.4
pip tensorflow-cpu >= 2.9.0, < 2.9.3 2.9.3
pip tensorflow-gpu >= 2.9.0, < 2.9.3 2.9.3
pip tensorflow-cpu >= 2.10.0, < 2.10.1 2.10.1
pip tensorflow-gpu >= 2.10.0, < 2.10.1 2.10.1

Exploit Probability

EPSS
0.17%
Percentile
37.38%

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.