CVE-2021-29612: TensorFlow - Heap Buffer Overflow in BandedTriangularSolve
Summary
CVE-2021-29612: Heap buffer overflow in BandedTriangularSolve. Affects tensorflow across 4 version ranges.
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
Fixed in 4 releases; the minimum fixed version depends 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-2021-29612 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 developing and deploying machine learning models. TensorFlow is widely used in various industries and research domains due to its flexibility and scalability. However, a vulnerability has been discovered in the implementation of tf.raw_ops.BandedTriangularSolve in TensorFlow.
Vulnerability Detail
The vulnerability arises from a heap buffer overflow in the Eigen implementation of tf.raw_ops.BandedTriangularSolve. The implementation fails to validate that the two input tensors are not empty, leading to a potential heap buffer overflow. Additionally, the validation present in the code is ineffective due to a missing check of the ctx->status() value. This vulnerability can be exploited by an attacker to execute arbitrary code or cause a denial-of-service condition. The impact of this vulnerability is rated as high.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 2.1.42.1.4 -
>= 2.2.0, < 2.2.32.2.3 -
>= 2.3.0, < 2.3.32.3.3 -
>= 2.4.0, < 2.4.22.4.2
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.
Conclusion
In conclusion, TensorFlow is affected by a heap buffer overflow vulnerability in the BandedTriangularSolve implementation. This vulnerability can be mitigated by updating to TensorFlow 2.5.0 or applying the fix on the affected versions. For further support on vulnerability remediation, you can contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides a comprehensive ecosystem for developing and deploying machine learning models.
The vulnerability can be exploited by an attacker to execute arbitrary code or cause a denial-of-service condition. The impact is rated as high.
To fix this vulnerability, update TensorFlow to version 2.5.0 or any subsequent version. Alternatively, you can apply the fix by cherrypicking the commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, or TensorFlow 2.1.4.
No specific workarounds have been provided for this vulnerability.
For more information about this vulnerability, you can refer to the provided source link in the vulnerability details.
References
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