Improve robustness in load_module and harden Dockerfile security

[RinZ27]

This PR addresses two areas for improvement identified during a security and logic audit:

1. Robustness in Module Loading: Replaced a bare except: block with except Exception: in tensorflow_quantum/core/ops/load_module.py. This ensures that critical system-level exceptions (like KeyboardInterrupt) are not unintentionally caught, improving the overall reliability of the operator loading logic.

2. Security Hardening for Release Dockerfile: Added a non-root user (tfq-user) to the release/docker/Dockerfile. Running containers as a non-privileged user is a standard security best practice to mitigate potential container breakout risks and adhere to the principle of least privilege.

Both changes are targeted and minimally invasive, focusing on practical correctness and security posture.

[gemini-code-assist]

Summary of Changes

Hello, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request enhances the project's stability and security posture by refining exception handling in the module loading mechanism and implementing a non-root user strategy within the Docker build process. These changes collectively reduce potential vulnerabilities and improve the reliability of core operations.

Highlights

• Module Loading Robustness: Replaced a bare except: block with except Exception: in tensorflow_quantum/core/ops/load_module.py to prevent unintentionally catching critical system-level exceptions, improving the reliability of operator loading.
• Dockerfile Security Hardening: Added a non-root user (tfq-user) to the release/docker/Dockerfile and switched to it, enhancing security by adhering to the principle of least privilege and mitigating potential container breakout risks.

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Changelog

• release/docker/Dockerfile
  • Added a non-root user tfq-user and switched to it for improved container security.
• tensorflow_quantum/core/ops/load_module.py
  • Updated a bare except block to except Exception for more specific and robust error handling during module loading.

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[gemini-code-assist]

Code Review

This pull request introduces two valuable improvements: making the module loading more robust by specifying the exception type, and enhancing Dockerfile security by adding a non-root user. Both changes are well-aligned with best practices. I have provided a couple of suggestions for further refinement. One suggestion aims to make the exception handling even more specific to improve debugging, and the other is to enhance the usability of the Docker container by setting a working directory for the new user.