CVE-2021-29530: TensorFlow-gpu - Null Pointer Dereference in SparseMatrixSparseCholesky
Summary
CVE-2021-29530: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-gpu across 5 version ranges.
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
< e6a7c7cc18c3aaad1ae0872cb0a959f5c923d2bd
Fixed in 4 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-cpu · PyPI
The same CVE-2021-29530 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
TensorFlow is an end-to-end open source platform for machine learning. It provides a comprehensive ecosystem of tools, libraries, and resources for developing and deploying machine learning models. TensorFlow-gpu is a variant of TensorFlow that leverages GPU acceleration for faster computation. It is widely used in various industries and research domains for deep learning tasks.
Vulnerability Detail
The vulnerability (CVE-2021-29530) in TensorFlow-gpu arises from a null pointer dereference in the tf.raw_ops.SparseMatrixSparseCholesky function. An attacker can exploit this vulnerability by supplying an invalid permutation argument to the function. The implementation fails to properly validate the input arguments, allowing the code to proceed even when the input is invalid. This can lead to a null pointer dereference, resulting in a crash or potentially allowing an attacker to execute arbitrary code. The vulnerability affects versions of TensorFlow-gpu up to and including 2.4.2.
How To Fix
Latest published version: 2.12.0 as of 22 Oct 2026
pip install --upgrade "tensorflow-gpu==2.12.0"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.
-
< 2.1.42.1.4pip install --upgrade "tensorflow-gpu==2.1.4" -
>= 2.2.0, < 2.2.32.2.3pip install --upgrade "tensorflow-gpu==2.2.3" -
>= 2.3.0, < 2.3.32.3.3pip install --upgrade "tensorflow-gpu==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow-gpu==2.4.2"
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Workaround
There is no known workaround for this vulnerability. It is recommended to apply the fix by upgrading to the patched version of TensorFlow-gpu.
Conclusion
The vulnerability (CVE-2021-29530) in TensorFlow-gpu exposes users to the risk of a null pointer dereference, which can lead to crashes or potential code execution by attackers. It is crucial to upgrade to the patched version of TensorFlow-gpu (2.5.0 or later) or apply the backported fixes to mitigate this vulnerability. For further assistance or support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow-gpu is a variant of TensorFlow that utilizes GPU acceleration for faster computation in machine learning tasks.
A null pointer dereference occurs when a program attempts to access or manipulate memory using a null pointer, resulting in a crash or undefined behavior.
An attacker can exploit this vulnerability by providing an invalid permutation argument to the tf.raw_ops.SparseMatrixSparseCholesky function in TensorFlow-gpu, causing a null pointer dereference and potentially enabling the execution of arbitrary code.
Versions of TensorFlow-gpu up to and including 2.4.2 are affected by this vulnerability.
Yes, the fix for this vulnerability is included in TensorFlow-gpu version 2.5.0. Backported fixes are also available for versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4.
References
Related vulnerabilities
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