CVE-2022-41891: Segfault in tf.raw_ops.TensorListConcat
Summary
CVE-2022-41891: Segfault in tf.raw_ops.TensorListConcat. 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-2022-41891 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
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Background
The TensorFlow package is an open-source machine learning framework developed by Google. It provides a comprehensive set of tools and libraries for building and deploying machine learning models. TensorFlow is widely used in various domains, including research, industry, and academia. However, a vulnerability has been discovered in the tf.raw_ops.TensorListConcat function, which can lead to a segmentation fault and potential denial of service attack.
Vulnerability Detail
The vulnerability arises when the tf.raw_ops.TensorListConcat function is called with element_shape=[]. This triggers a segmentation fault, which can be exploited to launch a denial of service attack. An attacker can craft a malicious input that triggers the segmentation fault, causing the TensorFlow application to crash and potentially disrupting its functionality. This vulnerability has a CVSS score of 4.8, indicating a moderate severity level.
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"
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Workaround
As a workaround, users can avoid calling the tf.raw_ops.TensorListConcat function with element_shape=[]. Instead, they can provide a non-empty element_shape parameter to prevent the segmentation fault. Here is an example of a modified code snippet:
import tensorflow as tf
tf.raw_ops.TensorListConcat(
input_handle=tf.data.experimental.to_variant(tf.data.Dataset.from_tensor_slices([1, 2, 3])),
element_dtype=tf.dtypes.float32,
element_shape=[1]
)
By specifying a non-empty element_shape, the vulnerability can be mitigated.
Conclusion
In conclusion, the tf.raw_ops.TensorListConcat function in TensorFlow is vulnerable to a segmentation fault when called with element_shape=[]. This can be exploited to launch a denial of service attack. Users should update their TensorFlow installation to one of the patched versions or apply the provided workaround. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open-source machine learning framework developed by Google. It provides tools and libraries for building and deploying machine learning models.
The vulnerability can be used to trigger a segmentation fault in TensorFlow, potentially leading to a denial of service attack.
To fix the vulnerability, update your TensorFlow installation to one of the patched versions: TensorFlow 2.8.4, TensorFlow 2.9.3, TensorFlow 2.10.1, or TensorFlow 2.11 (upcoming release).
Yes, you can avoid the vulnerability by providing a non-empty element_shape parameter when calling the tf.raw_ops.TensorListConcat function.
This vulnerability was reported by Tong Liu from ShanghaiTech University.
References
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