Segfault via tf.raw_ops.TensorListConcat element_shape=[] in TensorFlow <2.11
CVE-2022-41891 Published on November 18, 2022

Segfault in `tf.raw_ops.TensorListConcat` in Tensorflow
TensorFlow is an open source platform for machine learning. If `tf.raw_ops.TensorListConcat` is given `element_shape=[]`, it results segmentation fault which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit fc33f3dc4c14051a83eec6535b608abe1d355fde. 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-2022-41891 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-2022-41891. 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

Improper Input Validation

The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.


Products Associated with CVE-2022-41891

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Affected Versions

tensorflow:

Vulnerable Packages

The following package name and versions may be associated with CVE-2022-41891

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
0.16%
Percentile
36.41%

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.