GitHub security workshop: Add a deterministic CodeQL scanning lab

Goal

Teach learners how to enable code scanning and observe a real, intentionally introduced CodeQL finding in the pets application.

Scope

Add one safe training change that is detected reliably by a documented Python CodeQL query. The vulnerable path should be realistic enough to teach source-to-sink reasoning, but isolated from normal workshop startup and clearly marked as training-only. Provide a maintainer verification procedure so dependency or query-suite updates cannot silently break the exercise.

Acceptance criteria

• The exercise explains default setup versus advanced setup and selects one tested path.
• Learners enable CodeQL using current, capability-based instructions.
• A training fixture or guided code change triggers a named CodeQL query deterministically.
• The fixture contains no real secret, external side effect, or production deployment path.
• Learners trigger analysis on a branch or pull request and can identify the resulting check.
• The expected query ID, severity, file, and vulnerable data flow are documented for maintainers.
• A repeatable validation step proves the expected alert appears.
• Cleanup/reset instructions return the repository to a safe state.

Inizia esaminando l'applicazione pets e le istruzioni di configurazione esistenti del workshop, quindi confronta le opzioni di configurazione predefinita e avanzata di CodeQL. Definisci un fixture destinato esclusivamente alla formazione o una modifica guidata e documenta la query denominata, la gravità, il file, il flusso dei dati, il trigger del branch o della pull request, il passaggio di convalida e la procedura di pulizia. L'attività è completata quando l'avviso compare in modo affidabile senza secrets, effetti collaterali o un percorso di produzione.