CVE-2021-29574: TensorFlow - Null Pointer Dereference in MaxPool3DGradGrad
Summary
CVE-2021-29574: Undefined behavior in MaxPool3DGradGrad. Affects tensorflow across 4 version ranges.
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
Fixed in 4 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-29574 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 set of tools, libraries, and resources for building and deploying machine learning models. TensorFlow is widely used in various industries and research fields.
Vulnerability Detail
The implementation of tf.raw_ops.MaxPool3DGradGrad in TensorFlow exhibits a null pointer dereference vulnerability. This vulnerability occurs when the implementation fails to validate that the three tensor inputs are not empty. If any of these tensors are empty, accessing the elements in the tensor results in dereferencing a null pointer. An attacker can exploit this vulnerability by supplying empty tensors as inputs to the MaxPool3DGradGrad operation. The impact of this vulnerability can lead to undefined behavior, potentially resulting in denial of service or arbitrary code execution.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 2.1.42.1.4 -
>= 2.2.0, < 2.2.32.2.3 -
>= 2.3.0, < 2.3.32.3.3 -
>= 2.4.0, < 2.4.22.4.2
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
There is no known workaround for this vulnerability at the moment.
Conclusion
The vulnerability in TensorFlow's MaxPool3DGradGrad operation can lead to undefined behavior and potential security risks. It is crucial for users to update their TensorFlow installations to the fixed versions to mitigate the vulnerability. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning, widely used for building and deploying machine learning models.
This vulnerability can lead to undefined behavior, potentially resulting in denial of service or arbitrary code execution.
TensorFlow versions 2.1.4, 2.2.3, 2.3.3, and 2.4.2 are affected by this vulnerability.
There is currently no known workaround for this vulnerability.
Users are advised to update their TensorFlow installations to the fixed versions (2.5.0, 2.4.2, 2.3.3, 2.2.3, or 2.1.4) as soon as they are available.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
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