CVE-2021-37660: TensorFlow Division by Zero Vulnerability
Summary
CVE-2021-37660: Division by 0 in inplace operations in TensorFlow. Affects tensorflow across 3 version ranges.
>= 2.3.0, < 2.3.4
>= 2.4.0, < 2.4.3
>= 2.5.0, < 2.5.1
Fixed in 2.3.4, 2.4.3 or 2.5.1, depending 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-2021-37660 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 industries and research fields for tasks such as image recognition, natural language processing, and recommendation systems. However, a vulnerability has been discovered in TensorFlow that allows an attacker to trigger a floating point exception by exploiting a logic error in inplace operations. This vulnerability affects versions 2.3.0 to 2.6.0-rc2 of TensorFlow.
Vulnerability Detail
The vulnerability arises from a logic error in the implementation of inplace operations in TensorFlow. When certain crafted arguments are passed to inplace operations, a division by zero occurs, resulting in a floating point exception. This can be exploited by an attacker to cause a denial of service (DoS) condition or potentially execute arbitrary code. The issue has been identified and patched in the GitHub commit e86605c0a336c088b638da02135ea6f9f6753618. The fix will be included in TensorFlow 2.6.0 and has also been backported to versions 2.5.1, 2.4.3, and 2.3.4.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
>= 2.3.0, < 2.3.42.3.4 -
>= 2.4.0, < 2.4.32.4.3 -
>= 2.5.0, < 2.5.12.5.1
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Workaround
There is no known workaround for this vulnerability. It is essential to apply the provided fix by updating TensorFlow to the patched versions.
Conclusion
The TensorFlow Division by Zero Vulnerability (CVE-2021-37660) poses a risk to systems running affected versions of TensorFlow. It is crucial to update to the patched versions to mitigate the vulnerability. Failure to do so may result in a denial of service (DoS) condition or potential execution of arbitrary code. For further assistance or support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides tools and libraries for developing and deploying machine learning models.
The vulnerability allows an attacker to trigger a floating point exception in TensorFlow, potentially leading to a denial of service (DoS) condition or arbitrary code execution.
Versions 2.3.0 to 2.6.0-rc2 of TensorFlow are affected by this vulnerability.
Yes, the vulnerability has been patched in the GitHub commit e86605c0a336c088b638da02135ea6f9f6753618. The fix will be included in TensorFlow 2.6.0 and has also been backported to versions 2.5.1, 2.4.3, and 2.3.4.
To fix the vulnerability, update TensorFlow to the latest patched version. Follow the provided instructions in the 'how_to_fix' section of this report.
References
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