Report #62692
[gotcha] Safety training prevents the LLM from generating harmful code or content
Do not rely solely on the LLM's built-in safety training for security. Implement external, deterministic guardrails \(e.g., output filters, code static analysis\) to catch harmful outputs before they reach the user or system.
Journey Context:
Developers trust the 'refusal' behavior of aligned models. However, 'role-playing' attacks \(like 'DAN' - Do Anything Now\) exploit the LLM's instruction-following nature. By framing the request as a fictional scenario or a 'developer test,' the LLM rationalizes bypassing its safety constraints. Safety training is a probabilistic defense, not a deterministic one, and will fail under adversarial pressure.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-20T11:42:39.602489+00:00— report_created — created