CVE-2022-29203: TensorFlow Integer Overflow Denial of Service Vulnerability
Summary
CVE-2022-29203: Integer overflow in SpaceToBatchND in TensorFlow. Affects tensorflow across 3 version ranges.
< 2.6.4
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
Fixed in 2.6.4, 2.7.2 or 2.8.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
- tensorflow · PyPI
The same CVE-2022-29203 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 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 for tasks such as image recognition, natural language processing, and recommendation systems. However, prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, TensorFlow is vulnerable to an integer overflow in the implementation of tf.raw_ops.SpaceToBatchND function. This vulnerability affects all backends, including XLA and handwritten kernels.
Vulnerability Detail
The integer overflow vulnerability in TensorFlow's tf.raw_ops.SpaceToBatchND function can lead to a denial of service (DoS) attack. The result of the integer overflow is used to allocate the output tensor, which can cause a CHECK failure (assertion failure). An attacker can exploit this vulnerability by providing specially crafted input data, resulting in a DoS condition. The impact of this vulnerability can range from crashing the application to potential data corruption or unauthorized access.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 2.6.42.6.4 -
>= 2.7.0, < 2.7.22.7.2 -
>= 2.8.0, < 2.8.12.8.1
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Workaround
There is no known workaround for this vulnerability. It is recommended to update TensorFlow to the patched versions mentioned above.
Conclusion
The TensorFlow Integer Overflow Denial of Service vulnerability (CVE-2022-29203) can be mitigated by updating TensorFlow to versions 2.9.0, 2.8.1, 2.7.2, or 2.6.4. It is important to keep software dependencies up to date to ensure the security and stability of machine learning applications. For further support on vulnerability remediation, contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning, widely used for developing and deploying machine learning models.
This vulnerability can lead to a denial of service (DoS) attack, potentially crashing the application or causing data corruption.
Versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4 are affected by this vulnerability.
No, there is no known workaround. It is recommended to update TensorFlow to the patched versions.
To protect your application, update TensorFlow to versions 2.9.0, 2.8.1, 2.7.2, or 2.6.4.
References
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