CVE-2022-23560: TensorFlow - Limited Reads and Writes Outside of Arrays
Summary
CVE-2022-23560: Read and Write outside of bounds in TFLite. 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-2022-23560 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 allows an attacker to craft a TFLite model, enabling limited reads and writes outside of arrays in TFLite. This vulnerability arises due to missing validation in the conversion from sparse tensors to dense tensors.
Vulnerability Detail
The vulnerability in TensorFlow (CVE-2022-23560) allows an attacker to exploit the conversion process from sparse tensors to dense tensors in TFLite models. By crafting a malicious TFLite model, the attacker can perform limited reads and writes outside of arrays, potentially leading to unauthorized access or modification of sensitive data. This vulnerability affects TensorFlow versions 2.5.2, 2.6.0, and 2.7.0. It has been assigned a CVSSv3 severity score of 9.8 (Critical).
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
There is no known workaround for this vulnerability. It is essential to apply the provided fixes or upgrades to ensure the security of TensorFlow installations.
Conclusion
The vulnerability in TensorFlow (CVE-2022-23560) allows an attacker to perform limited reads and writes outside of arrays in TFLite models. It is crucial to upgrade to the fixed versions or apply the provided patches to ensure the security of TensorFlow installations. 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.
This vulnerability allows an attacker to perform limited reads and writes outside of arrays in TFLite models, potentially leading to unauthorized access or modification of sensitive data.
TensorFlow versions 2.5.2, 2.6.0, and 2.7.0 are affected by this vulnerability.
This vulnerability has been assigned a CVSSv3 severity score of 9.8 (Critical).
To fix this vulnerability, it is recommended to upgrade to TensorFlow version 2.8.0. Patches are also available for TensorFlow versions 2.7.1, 2.6.3, and 2.5.3.
References
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