CVE-2021-29558: Heap buffer overflow in tensorflow
Summary
CVE-2021-29558: Heap buffer overflow in SparseSplit. 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 · Bitnami
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-29558 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 open-source machine learning framework developed by Google. It provides a comprehensive ecosystem of tools, libraries, and resources 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 TensorFlow that could potentially lead to a heap buffer overflow.
Vulnerability Detail
The vulnerability, identified as CVE-2021-29558, specifically affects the SparseSplit function in TensorFlow. An attacker can exploit this vulnerability by providing malicious input to the function, causing a heap buffer overflow. This occurs due to the implementation accessing an array element based on a user-controlled offset. As a result, the attacker can override values on the heap, potentially leading to arbitrary code execution or a denial of service.
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.
-
< 2.1.42.1.4pip install --upgrade "tensorflow==2.1.4" -
>= 2.2.0, < 2.2.32.2.3pip install --upgrade "tensorflow==2.2.3" -
>= 2.3.0, < 2.3.32.3.3pip install --upgrade "tensorflow==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow==2.4.2"
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Workaround
As a temporary workaround, you can mitigate the risk by avoiding the usage of the SparseSplit function or by carefully validating and sanitizing the input provided to the function. Here is an example of how to avoid using the vulnerable function:
import tensorflow as tf
# Instead of using tf.raw_ops.SparseSplit, consider an alternative approach
# that achieves the desired functionality without the vulnerability.
# Example code:
# Your alternative code here
Conclusion
In conclusion, the vulnerability CVE-2021-29558 in TensorFlow poses a risk of heap buffer overflow. It is crucial to update to the patched versions of TensorFlow to mitigate this vulnerability. If you require further assistance or support in addressing this vulnerability, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open-source machine learning framework developed by Google. It provides a comprehensive ecosystem of tools, libraries, and resources for building and deploying machine learning models.
A heap buffer overflow is a type of vulnerability where a program writes data beyond the allocated memory buffer in the heap. This can lead to memory corruption, crashes, or even arbitrary code execution.
The vulnerability can be exploited by providing malicious input to the SparseSplit function in TensorFlow, causing a heap buffer overflow. This can be done by an attacker with the ability to control the input data.
The potential consequences of this vulnerability include arbitrary code execution, denial of service, or other forms of memory corruption. These can lead to the compromise of the affected system or disruption of its functionality.
To protect your system, it is recommended to update TensorFlow to the latest patched version. Additionally, you can follow secure coding practices, such as input validation and sanitization, to minimize the risk of exploitation.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
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