CVE-2022-21733: TensorFlow - Denial of Service Vulnerability
Summary
CVE-2022-21733: Memory exhaustion in Tensorflow. Affects tensorflow across 3 version ranges.
< 2.5.3
>= 2.6.0, < 2.6.3
>= 2.7.0, < 2.7.1
Fixed in 2.5.3, 2.6.3 or 2.7.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-gpu · PyPI
- tensorflow-cpu · PyPI
The same CVE-2022-21733 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 can lead to a denial of service attack.
Vulnerability Detail
The vulnerability (CVE-2022-21733) in TensorFlow arises from an integer overflow in the implementation of the StringNGrams function. This vulnerability can be exploited to trigger an out of memory condition, causing a denial of service. The issue stems from a lack of validation on the pad_width parameter, resulting in the computation of a negative value for ngram_width. This negative value is later used to allocate parts of the output, leading to the out of memory condition. The impact of this vulnerability can be significant, as it can disrupt the availability of TensorFlow-based applications and services.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 2.5.32.5.3 -
>= 2.6.0, < 2.6.32.6.3 -
>= 2.7.0, < 2.7.12.7.1
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
No specific workaround has been mentioned for this vulnerability. The recommended course of action is to apply the available patches or updates to TensorFlow as soon as they are released.
Conclusion
The vulnerability in TensorFlow (CVE-2022-21733) can lead to a denial of service attack by triggering an out of memory condition. It is crucial for users of TensorFlow to update their installations to the latest patched version as soon as it becomes available. This will ensure the security and availability of TensorFlow-based applications and services. For further support on vulnerability remediation, 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.
The vulnerability in TensorFlow can be exploited to trigger a denial of service attack, causing an out of memory condition and disrupting the availability of TensorFlow-based applications and services.
The vulnerability affects TensorFlow versions 2.5.2, 2.6.0, and 2.7.0. However, the issue has been addressed in TensorFlow 2.5.3, 2.6.2, 2.7.1, and will be fixed in the upcoming TensorFlow 2.8.0 release.
To fix this vulnerability, users should update their TensorFlow installations to the latest patched version as soon as it becomes available. Follow the official upgrade instructions provided by TensorFlow for the specific version you are using.
No specific workaround has been mentioned for this vulnerability. Applying the available patches or updates to TensorFlow is the recommended course of action.
References
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