CVE-2021-29535: TensorFlow Heap Buffer Overflow in QuantizedMul
Summary
CVE-2021-29535: TensorFlow is an end-to-end open source platform for machine learning. Affects tensorflow-cpu across 5 version ranges.
>= 2.2.0, < 2.3.0rc0
< 2.2.0rc0
>= 2.3.0, < 2.3.4
>= 2.4.0, < 2.4.3
< efea03b38fb8d3b81762237dc85e579cc5fc6e87
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-gpu · PyPI
The same CVE-2021-29535 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 is widely used in various domains, including research, industry, and academia. The package 'tensorflow-cpu' is a Python package that provides CPU-only support for TensorFlow. It is commonly used when running TensorFlow on systems without GPU capabilities.
Vulnerability Detail
The vulnerability (CVE-2021-29535) in TensorFlow's 'QuantizedMul' function allows an attacker to trigger a heap buffer overflow by passing invalid thresholds for quantization. The implementation assumes that the four arguments passed to the function are valid scalars and directly accesses their numeric values. However, if any of these tensors is empty, accessing the element at position 0 results in a buffer overflow. This vulnerability can be exploited to execute arbitrary code or cause a denial-of-service condition. The issue affects versions of TensorFlow up to 2.4.3.
How To Fix
Latest published version: 2.21.0 as of 22 Oct 2026
pip install --upgrade "tensorflow-cpu==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.
-
< 2.2.0rc02.2.0rc0pip install --upgrade "tensorflow-cpu==2.2.0rc0" -
>= 2.2.0, < 2.3.0rc02.3.0rc0pip install --upgrade "tensorflow-cpu==2.3.0rc0" -
>= 2.3.0, < 2.3.42.3.4pip install --upgrade "tensorflow-cpu==2.3.4" -
>= 2.4.0, < 2.4.32.4.3pip install --upgrade "tensorflow-cpu==2.4.3"
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. It is recommended to apply the fix by updating to the latest version of TensorFlow.
Conclusion
The vulnerability (CVE-2021-29535) in TensorFlow's 'QuantizedMul' function can be exploited to trigger a heap buffer overflow. It is crucial to update TensorFlow to the latest version (2.5.0) or apply the provided fix to mitigate the risk. For further assistance or support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-cpu →
FAQ
TensorFlow is an open source platform for machine learning that provides a comprehensive set of tools and resources for developing and deploying machine learning models.
'QuantizedMul' is a function in TensorFlow that performs element-wise multiplication on quantized tensors. It is commonly used in machine learning models that involve quantization.
The vulnerability occurs when invalid thresholds for quantization are passed to the 'QuantizedMul' function. This triggers a heap buffer overflow due to incorrect assumptions about the input tensors.
The vulnerability can be exploited by an attacker to execute arbitrary code or cause a denial-of-service condition. This can lead to unauthorized access, data leakage, or disruption of service.
To protect your system, it is recommended to update TensorFlow to the latest version that includes the fix for this vulnerability. Additionally, follow best practices for secure software development and deployment.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-cpu.
