Key takeaways

AI reconnaissance occurs when modern assistants block direct requests for sensitive data but routinely leak critical operational context — such as capabilities, boundaries, and tool access — in response to simple, benign-looking questions.

Mapping the attack surface using this leaked context allows attackers to design highly targeted, application-specific prompt injections that bypass standard model-level safety.

The need for runtime protection is urgent, as relying solely on static system prompts and model tuning is no longer enough.

Securing deployed AI applications requires dynamic guardrails capable of detecting early-stage probing in the attack kill chain, before an exploit occurs.

AI-based applications and assistants are becoming a new application attack surface.…