CVE-2021-29520: TensorFlow - Missing Validation in Conv3DBackprop Operations
Summary
CVE-2021-29520: Heap buffer overflow in Conv3DBackprop*. 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-2021-29520 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 due to its flexibility and scalability. However, a vulnerability has been identified in TensorFlow that affects versions 0 and 2.1.4 to 2.4.2. This vulnerability is related to missing validation between arguments in tf.raw_ops.Conv3DBackprop* operations, which can lead to heap buffer overflows.
Vulnerability Detail
The vulnerability arises from the lack of validation between the input, filter_sizes, and out_backprop tensors in tf.raw_ops.Conv3DBackprop* operations. The implementation assumes that these tensors have the same shape and are accessed in parallel. However, if the shapes of these tensors differ, it can result in a heap buffer overflow. An attacker could exploit this vulnerability to execute arbitrary code or cause a denial of service. The impact of this vulnerability is considered 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 mentioned for this vulnerability.
Conclusion
In conclusion, TensorFlow versions 0 and 2.1.4 to 2.4.2 are vulnerable to a heap buffer overflow due to missing validation in tf.raw_ops.Conv3DBackprop* operations. This vulnerability can be mitigated by upgrading to TensorFlow 2.5.0 or one of the backported versions. If you require further assistance or support in addressing this vulnerability, please 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 building and deploying machine learning models.
The impact of this vulnerability is considered high. It can lead to heap buffer overflows, allowing an attacker to execute arbitrary code or cause a denial of service.
Versions 0 and 2.1.4 to 2.4.2 of TensorFlow are affected by this vulnerability.
To fix this vulnerability, it is recommended to upgrade to TensorFlow 2.5.0 or later. Alternatively, you can upgrade to one of the backported versions: 2.1.4, 2.2.3, 2.3.3, or 2.4.2.
No specific workaround has been mentioned for this vulnerability.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
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