CVE-2021-37655: TensorFlow - Out-of-Bounds Read Vulnerability
Summary
CVE-2021-37655: Heap OOB in ResourceScatterUpdate in TensorFlow. Affects tensorflow across 3 version ranges.
>= 2.3.0, < 2.3.4
>= 2.4.0, < 2.4.3
>= 2.5.0, < 2.5.1
Fixed in 2.3.4, 2.4.3 or 2.5.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-37655 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 end-to-end open source platform for machine learning. It provides a comprehensive ecosystem for building and deploying machine learning models. TensorFlow is widely used in various industries and research domains.
Vulnerability Detail
The vulnerability (CVE-2021-37655) in TensorFlow allows an attacker to trigger a read from outside the bounds of heap allocated data by sending invalid arguments to the tf.raw_ops.ResourceScatterUpdate function. The issue arises due to incomplete validation of the relationship between the shapes of indices and updates tensors. Instead of checking that the shape of indices is a prefix of the shape of updates, the code only verifies the divisibility relationship between the number of elements in these tensors. This incomplete validation can lead to out-of-bounds memory access.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
>= 2.3.0, < 2.3.42.3.4 -
>= 2.4.0, < 2.4.32.4.3 -
>= 2.5.0, < 2.5.12.5.1
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 advised to update to the patched versions of TensorFlow as mentioned in the 'how_to_fix' section.
Conclusion
The vulnerability in TensorFlow (CVE-2021-37655) allows for out-of-bounds memory access, which can have serious security implications. It is crucial to update to the patched versions or apply the provided fix to ensure the correct validation of tensor shapes. For further support on vulnerability remediation, you can reach out to DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning, widely used for building and deploying machine learning models.
This vulnerability allows an attacker to trigger out-of-bounds memory access, which can potentially lead to information disclosure or code execution.
Versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, 2.5.0, 2.6.0-rc0, 2.6.0-rc1, and 2.6.0-rc2 are affected by this vulnerability.
You can use Vulert's playground (https://vulert.com/scanner) to check if your application is affected by this vulnerability. Simply upload your package-lock.json file to the playground and it will provide real-time alerts for open-source vulnerabilities.
Yes, the fix for this vulnerability is available in TensorFlow versions 2.6.0, 2.5.1, 2.4.3, and 2.3.4. It is recommended to update to the latest patched version.
References
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