CVE-2021-37654: TensorFlow - Out-of-Bounds Read Vulnerability
Summary
CVE-2021-37654: Heap OOB and CHECK fail in ResourceGather 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-2021-37654 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 of tools, libraries, and resources for building 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, a vulnerability has been discovered in TensorFlow that can lead to an out-of-bounds read issue.
Vulnerability Detail
The vulnerability (CVE-2021-37654) in TensorFlow allows an attacker to trigger a crash or read data from outside the bounds of heap allocated buffer. In debug builds of TensorFlow, the issue can be triggered by using tf.raw_ops.ResourceGather. In release builds, the vulnerability can be exploited by supplying a batch_dims value that is greater than or equal to the rank of the input tensor in the same API. This can result in reading data from outside the allocated buffer, potentially leading to information disclosure or a denial of service (DoS) condition.
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 specific workaround provided for this vulnerability. It is recommended to update to the patched versions of TensorFlow as mentioned in the 'how_to_fix' section.
Conclusion
The vulnerability in TensorFlow (CVE-2021-37654) can be mitigated by updating to the patched versions of TensorFlow. It is important to stay up-to-date with security patches to ensure the integrity and security of machine learning models and applications. 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 that provides tools and libraries for building and deploying machine learning models.
The vulnerability can lead to a crash or information disclosure in debug builds of TensorFlow. In release builds, it can result in reading data from outside the allocated buffer, potentially leading to information disclosure or a denial of service (DoS) condition.
The vulnerability affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, 2.5.0, and 2.6.0-rc0 to 2.6.0-rc2.
To fix this vulnerability, it is recommended to update to the patched versions of TensorFlow (2.6.0 or the cherrypicked versions for older releases).
No specific workaround is provided for this vulnerability. Updating to the patched versions is the recommended solution.
References
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