AI InfoSec Lab expects all collaboration to stay technical, respectful, and evidence-driven.
- Critique ideas, code, and experiments without attacking people.
- Keep discussions grounded in reproducible evidence and clear reasoning.
- Respect confidentiality for private repositories, datasets, and evaluation artifacts.
- Flag uncertainty, risk, and security concerns directly instead of hiding them.
- Harassment, discrimination, intimidation, or personal attacks.
- Sharing private organizational material outside approved channels.
- Intentionally misleading experiment reports or hiding regressions.
- Repeatedly bypassing repository safeguards without a documented reason.
- For conduct issues inside the organization, contact
@zzragidadirectly. - If the report concerns a repository maintainer, raise it privately to an organization admin instead of opening a public issue.
Organization admins may edit, lock, or remove content and may suspend access when behavior puts collaborators, repositories, or users at risk.