Automated Framework to Evaluate and Harden LLM System Instructions against Encoding Attacks

ArXi:2604.01039v1 Announce Type: cross System Instructions in Large Language Models (LLMs) are commonly used to enforce safety policies, define agent behavior, and protect sensitive operational context in agentic AI applications. These instructions may contain sensitive information such as API credentials, internal policies, and privileged workflow definitions, making system instruction leakage a critical security risk highlighted in the OWASP Top 10 for LLM Applications.