Voting, Validation, and Vulnerability in Local Language Model Penetration Testing An Empirical Study of Module Selection Under Adversarial Evidence
Small local language models are attractive for privacy-preserving penetration-testing assistants, but their module choices must remain reliable when target-controlled banners contain misleading or instruction-like text. We evaluate module selection in three experiments on an Apple M2 system with 8 GB of memory. A verif...