CVE-2022-29200: TensorFlow - Denial of Service Vulnerability
Summary
CVE-2022-29200: Missing validation causes denial of service in TensorFlow via LSTMBlockCell. 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-2022-29200 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 and research domains 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 a denial of service attack due to a lack of input validation in the implementation of tf.raw_ops.LSTMBlockCell.
Vulnerability Detail
The vulnerability arises from the incomplete validation of input arguments in the tf.raw_ops.LSTMBlockCell function. This allows an attacker to trigger a CHECK-failure, leading to a denial of service attack. The issue stems from the failure to validate the ranks of the tensor arguments, resulting in CHECK-failures when accessing the tensor elements. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 have been patched to address this vulnerability.
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 specific workaround available for this vulnerability. It is advised to update to the patched versions of TensorFlow as mentioned in the 'how_to_fix' section.
Conclusion
The vulnerability in TensorFlow allows an attacker to trigger a denial of service attack by exploiting the incomplete input validation in the tf.raw_ops.LSTMBlockCell function. To mitigate this vulnerability, it is crucial to update TensorFlow to the patched versions mentioned. For further assistance and support in 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 developing and deploying machine learning models.
The vulnerability allows an attacker to trigger a denial of service attack, potentially disrupting the availability of TensorFlow-based applications.
Versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4 are affected by this vulnerability.
To fix this vulnerability, update TensorFlow to version 2.9.0, 2.8.1, 2.7.2, or 2.6.4.
No, there is no specific workaround available. Updating to the patched versions is the recommended solution.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
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