Tadayoshi Kohno

It is argued that self-modifying coding agents must be designed to be more resilient to such attacks, and properties of the vulnerability, benchmark, model, and agent scaffolding that are sufficient to enable a benchmark poisoning attack are distill.

Existing AI agent permissioning schemes are hard to compare, so this paper provides a formal foundation and reveals a fundamental conflict between training data confidentiality and agent completeness.