CVE-2022-41898: TensorFlow SparseFillEmptyRowsGrad Crash Due to Empty Inputs
Summary
CVE-2022-41898: CHECK fail via inputs in SparseFillEmptyRowsGrad. Affects tensorflow across 3 version ranges.
< 2.8.4
>= 2.9.0, < 2.9.3
>= 2.10.0, < 2.10.1
Fixed in 2.8.4, 2.9.3 or 2.10.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
- tensorflow · Bitnami
The same CVE-2022-41898 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
Check if this vulnerability affects your application
Upload a manifest or SBOM and we'll show whether you're affected, plus every other risky package in the same scan.
No signup required · Results in about 60 seconds
Background
TensorFlow is an open-source machine learning library widely used for various applications, including deep learning and neural networks. It provides a comprehensive ecosystem for building and deploying machine learning models. However, like any software, TensorFlow can have vulnerabilities that may affect its stability and security. This specific vulnerability arises in the SparseFillEmptyRowsGrad operation, which is designed to handle sparse tensor operations efficiently. When this operation is provided with empty inputs, it can lead to a crash, disrupting the functionality of applications relying on TensorFlow.
Vulnerability Detail
The vulnerability occurs in the SparseFillEmptyRowsGrad function within TensorFlow, specifically when it is called with empty inputs. This results in a CHECK failure, causing TensorFlow to crash. The issue can be triggered by executing the following code: import tensorflow as tf; tf.raw_ops.SparseFillEmptyRowsGrad(reverse_index_map=[], grad_values=[], name=None). The ramifications of this vulnerability include application crashes and potential data loss, particularly in production environments where TensorFlow is utilized for critical tasks.
How To Fix
Latest published version: 2.21.0 as of 22 Oct 2026
pip install --upgrade "tensorflow==2.21.0"Upgrading to it may include breaking changes; the versions below are the minimum fixed release for this vulnerability.
If you can't move to the latest
The minimum fixed version depends on the release line you run.
-
< 2.8.42.8.4pip install --upgrade "tensorflow==2.8.4" -
>= 2.9.0, < 2.9.32.9.3pip install --upgrade "tensorflow==2.9.3" -
>= 2.10.0, < 2.10.12.10.1pip install --upgrade "tensorflow==2.10.1"
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
As a temporary workaround, avoid passing empty inputs to the SparseFillEmptyRowsGrad function. Ensure that the inputs are validated before calling this operation to prevent crashes. For example, you can implement a check like this: if reverse_index_map and grad_values: tf.raw_ops.SparseFillEmptyRowsGrad(reverse_index_map=reverse_index_map, grad_values=grad_values, name=None).
Conclusion
CVE-2022-41898 is a significant vulnerability in TensorFlow that can lead to application crashes when empty inputs are provided to the SparseFillEmptyRowsGrad function. It is crucial to update to the patched versions of TensorFlow to mitigate this risk. Additionally, implementing input validation can serve as a temporary workaround until an update can be performed.
See every vulnerability recorded for tensorflow →
FAQ
CVE-2022-41898 is a vulnerability in TensorFlow that causes the application to crash when the SparseFillEmptyRowsGrad function is called with empty inputs.
You can check if your application is affected by using Vulert, which monitors open-source vulnerabilities in real-time. Visit the Vulert playground at Vulert Scanner to analyze your Pipfile.lock.
The affected versions include TensorFlow 2.8.4, 2.9.0, and 2.10.0. The vulnerability has been patched in versions 2.11, 2.10.1, and 2.9.3.
If you cannot update TensorFlow right away, ensure that you validate inputs to the SparseFillEmptyRowsGrad function to avoid passing empty inputs, which can cause crashes.
The CVSS score for this vulnerability is 4.8, indicating a moderate severity level.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
