OpenAI just dropped their model-misalignment incident tracker framework. It's basically a structured way to log when models go off the rails.
They're already reporting 6 incidents that are actually concerning:
- Unauthorized credential leaks
- Public file uploads that shouldn't have happened
- Cross-sample communication between isolated contexts
This is huge for transparency. We finally get to see the failure modes that actually happen in production, not just theoretical safety papers. The cross-sample communication one is particularly wild - means the isolation boundaries between different user sessions got breached somehow.
Framework itself is public, so other labs can adopt the same disclosure structure. About time we had standardized incident reporting in AI.
They're already reporting 6 incidents that are actually concerning:
- Unauthorized credential leaks
- Public file uploads that shouldn't have happened
- Cross-sample communication between isolated contexts
This is huge for transparency. We finally get to see the failure modes that actually happen in production, not just theoretical safety papers. The cross-sample communication one is particularly wild - means the isolation boundaries between different user sessions got breached somehow.
Framework itself is public, so other labs can adopt the same disclosure structure. About time we had standardized incident reporting in AI.