Use cryptographically secure random for new document ids

[probicheaux]

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Fixes #1161

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[gemini-code-assist]

Summary of Changes

Hello @probicheaux, 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 significantly improves the security posture of automatically generated Firestore document IDs by switching to a cryptographically secure random number generator. This change ensures that document IDs are more robust against prediction and potential exploits, while also maintaining compatibility with diverse operating environments through a thoughtful fallback mechanism.

Highlights

• Enhanced Security for Document IDs: The generation of new document IDs now utilizes random.SystemRandom, a cryptographically secure pseudo-random number generator, to improve the unpredictability and security of auto-generated IDs.
• Robust Fallback Mechanism: A try-except block has been introduced to handle NotImplementedError that might occur on very old Unix systems lacking os.urandom. In such cases, the system gracefully falls back to using random.choice.

Changelog

• google/cloud/firestore_v1/base_collection.py
  • Imported random.SystemRandom and initialized a global instance system_random for use in ID generation.
  • Modified the _auto_id function to use system_random.choice for selecting characters, ensuring cryptographic randomness.
  • Wrapped the system_random.choice call in a try-except NotImplementedError block to provide a fallback to random.choice if os.urandom is not available on the system.

Activity

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[gemini-code-assist]

Code Review

This pull request improves security by using a cryptographically secure random number generator (random.SystemRandom) for creating new document IDs. The change includes a fallback to the standard random module for compatibility with older systems.

However, the unit tests for _auto_id have not been updated to reflect this change, which is a critical issue that needs to be addressed. I've also included a suggestion to refactor the _auto_id function to reduce code duplication and improve maintainability.

[gemini-code-assist]

The existing unit test test__auto_id in tests/unit/v1/test_base_collection.py mocks random.choice. With this change, the test will likely fail as the code now primarily calls system_random.choice. The tests need to be updated to cover both the primary path (using system_random.choice) and the fallback path (using random.choice when NotImplementedError is raised).

[probicheaux]

Fixed

[gemini-code-assist]

While the current implementation is correct, it contains duplicated code for generating the random string. To improve maintainability, you could refactor this to select the appropriate random function first, and then use it to generate the string.

    try:
        # Use a cryptographically secure random number generator if available.
        # The .random() method will raise NotImplementedError on systems without os.urandom().
        system_random.random()
        choice_func = system_random.choice
    except NotImplementedError:
        # Fallback to the default pseudo-random generator on very old systems.
        choice_func = random.choice

    return "".join(choice_func(_AUTO_ID_CHARS) for _ in range(20))

[probicheaux]

this is slower

[PranavMin]

I agree, this is slower

[daniel-sanche]

The change looks good to me, but I think the coverage check will likely fail, because the new except case isn't covered by unit tests. So you'll likely have to add a new one, with random.SystemRandom mocked to raise an exception

I triggered the CI tests, so we'll see what comes up

Thanks for submitting this

[probicheaux]

@daniel-sanche Thanks for taking a look. I've added a test that makes random.SystemRandom.choice raise NotImplementedError. Tests pass locally.