The AI backdoor your security stack is not built to see

Enterprises deploying LLMs have spent the past two years building defenses around a reasonable assumption: malicious behavior leaves a trace in the input. Scan for suspicious tokens, filter unusual characters, watch for prompt injection patterns. New research from Microsoft and the Institute of Science Tokyo demonstrates that this defensive posture has a blind spot, and the cost of that blind spot could be measured in leaked proprietary data and regulatory exposure.