Request for support for Protobuf Java 4.x.x (specifically 4.32.1) in TensorFlow Java

Bắt đầu bằng việc xem xét thiết lập dependency của TensorFlow Java và khả năng tương thích của nó với phía Python được mô tả trong issue. So sánh khả năng hỗ trợ protobuf Java 3.21.9 hiện tại với khả năng hỗ trợ 4.32.1 được yêu cầu, bao gồm cả hành vi liên quan đến descriptor; được xem là hoàn tất khi khả năng tương thích cho thiết lập Java/Python hybrid được ghi lại và hoạt động đúng.

Please make sure that this is a feature request. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:feature_template

Hi Everyone 👋

I have a project where I am using a java/python hybrid of Tensorflow in a Machine Learning. My project was based on

System information

• TensorFlow version (you are using): 1.2.0-SNAPSHOT
• Are you willing to contribute it (Yes/No): No

Describe the feature and the current behavior/state.

In my project, I am working with a hybrid TensorFlow setup using both Python and Java. The Python side uses TensorFlow 2.15 and protobuf 3.20.3, while the Java side uses TensorFlow 0.5.0 and protobuf 3.21.7.
Due to a security vulnerability (CVE-2025-4565), I need to update the Python protobuf from 3.20.3 to 4.25.8. After upgrading, I encountered an intermittent issue stemming from descriptor changes between protobuf versions 3.x.x and 4.x.x. TensorFlow Python supports protobuf 4.25.8, but TensorFlow Java (1.2.0-SNAPSHOT) only supports protobuf Java 3.21.9.
Given that protobuf Java has since been updated (to version 4.32.1 as of this writing), I would like to request official support for protobuf Java 4.x.x, particularly 4.32.1, in TensorFlow Java to ensure compatibility with the updated Python side of my project.

Will this change the current api? How?

Yes, this change will require updating the dependencies in the TensorFlow Java ecosystem to include protobuf Java 4.x.x support. This update may involve changes to how descriptors and certain functions are handled, so users may need to adjust their code to accommodate those changes.

Who will benefit with this feature?

• Developers using TensorFlow in hybrid Python/Java environments.
• Developers who need to update to the latest protobuf versions for security (CVE-2025-4565) or compatibility with other libraries.
• Users facing compatibility issues due to mismatched versions of protobuf between Python and Java.

Any Other info.

The issue is critical as it directly impacts security and cross-platform compatibility. It would be beneficial if this update could be rolled into a future release of TensorFlow Java, or at least made available in a stable branch for users who rely on protobuf Java 4.x.x.