CVE-2022-41910: TensorFlow Out-of-Bounds Memory Read or Crash
Summary
CVE-2022-41910: Heap out of bounds read in QuantizeAndDequantizeV2 in Tensorflow. Affects tensorflow across 3 version ranges.
< 2.8.4
>= 2.9.0, < 2.9.3
>= 2.10.0, < 2.10.1
Fixed in 2.8.4, 2.9.3 or 2.10.1, 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-2022-41910 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 framework for building and training machine learning models. TensorFlow is widely used in various industries for tasks such as image recognition, natural language processing, and recommendation systems. This vulnerability affects versions 2.8.4, 2.9.3, and 2.10.0 of TensorFlow. The vulnerability allows for an out-of-bounds memory read or a crash when the sizes of inputs given to the MakeGrapplerFunctionItem function are greater than or equal to the sizes of the outputs.
Vulnerability Detail
The vulnerability arises in the MakeGrapplerFunctionItem function of TensorFlow. When the sizes of inputs provided to the function are greater than or equal to the sizes of the outputs, it triggers an out-of-bounds memory read or a crash. This can potentially lead to information disclosure or denial of service. The issue has been patched in the GitHub commit a65411a1d69edfb16b25907ffb8f73556ce36bb7 and will be included in TensorFlow 2.11.0. Additionally, the fix will be backported to TensorFlow versions 2.8.4, 2.9.3, and 2.10.1.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 2.8.42.8.4 -
>= 2.9.0, < 2.9.32.9.3 -
>= 2.10.0, < 2.10.12.10.1
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 update TensorFlow to the patched versions mentioned above.
Conclusion
In conclusion, TensorFlow versions 2.8.4, 2.9.3, and 2.10.0 are vulnerable to an out-of-bounds memory read or crash. It is crucial to update to TensorFlow 2.11.0 or apply the provided patch to mitigate this vulnerability. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides a framework for building and training machine learning models.
The vulnerability can lead to an out-of-bounds memory read or a crash, potentially resulting in information disclosure or denial of service.
Versions 2.8.4, 2.9.3, and 2.10.0 of TensorFlow are affected.
To fix this vulnerability, update TensorFlow to version 2.11.0 or apply the patch by cherrypicking the commit a65411a1d69edfb16b25907ffb8f73556ce36bb7 from the GitHub repository.
There is no known workaround for this vulnerability. It is recommended to update TensorFlow to the patched versions.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
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