AI-Case-Sorter-Py

Security Policy

Reporting a vulnerability

Please report security vulnerabilities privately. Do not open a public issue, pull request, or discussion for a suspected vulnerability.

Preferred: use GitHub’s private vulnerability reporting on this repository — the Security tab → Report a vulnerability. This opens a private advisory visible only to the maintainers. (Maintainers: enable this under Settings → Code security and analysis → Private vulnerability reporting.)

Alternative: email the maintainers at seth@sjseth.com.

Please include as much as you can:

• a description of the issue and its impact,
• steps to reproduce, or a proof of concept,
• the affected version or commit, and your platform (Windows / Linux).

What to expect

• We aim to acknowledge your report within a few days.
• We’ll investigate, keep you informed of progress, and credit you (if you’d like) when a fix is released.
• Please give us a reasonable window to ship a fix before any public disclosure.

Scope

This policy covers the desktop application in this repository. The hardware/firmware, the local model server, and the hosted community backend are separate projects — report issues in those to their respective maintainers.

Notes for users on untrusted content

A few things worth knowing about how the app handles content from others:

• Models can run code when loaded. The app loads PyTorch checkpoints with weights_only=True and warns before importing or downloading a model, but you should still only load models from sources you trust.
• Evaluation reports embed external data. The model evaluator generates a self-contained HTML report from the image folder you point it at; open reports only for folders you trust.
• Community sign-in is optional. The app runs fully offline; community features (sharing, downloads, the feedback loop) are the only network-gated surface and require you to sign in.

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