CVE-2021-37638: TensorFlow - Invalid Argument Null Pointer Dereference
Summary
CVE-2021-37638: Null pointer dereference in RaggedTensorToTensor 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-2021-37638 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
Check if this vulnerability affects your application
Upload a manifest or SBOM and we'll show whether you're affected, plus every other risky package in the same scan.
No signup required · Results in about 60 seconds
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 fields for tasks such as image recognition, natural language processing, and recommendation systems. However, a vulnerability has been discovered in TensorFlow that can lead to a null pointer dereference and undefined behavior when sending an invalid argument for the row_partition_types parameter of the tf.raw_ops.RaggedTensorToTensor API.
Vulnerability Detail
The vulnerability arises from the implementation of the tf.raw_ops.RaggedTensorToTensor API in TensorFlow. The implementation accesses the first element of a user-supplied list of values without validating that the list is not empty. This can result in a null pointer dereference when an empty list is provided as the argument for row_partition_types. An attacker could potentially exploit this vulnerability to cause a denial of service or execute arbitrary code in the context of the affected application. The issue has been patched in the latest versions of TensorFlow.
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 recommended to update TensorFlow to the latest patched version as mentioned in the 'how_to_fix' section.
Conclusion
The vulnerability in TensorFlow can lead to a null pointer dereference and undefined behavior. It is crucial to update TensorFlow to the latest patched version to mitigate this vulnerability. For further support on vulnerability remediation, 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 developing and deploying machine learning models.
The vulnerability can lead to a null pointer dereference and undefined behavior, potentially resulting in a denial of service or arbitrary code execution.
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.
Yes, the vulnerability has been patched in TensorFlow 2.6.0 and will also be backported to TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4.
No, there is no known workaround for this vulnerability. It is recommended to update TensorFlow to the latest patched version.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
