a companion resource to the Secure Software Development Framework to incorporate secure development practices for generative artificial intelligence and for foundation models. (F) Developing and publishing cybersecurity tools, methodologies, best practices, voluntary guidelines, and other supporting information to assist persons who maintain systems used to create or train artificial intelligence models to discover and mitigate vulnerabilities and attacks. (G) Coordinating or developing guidelines, metrics, benchmarks, and methodologies for evaluating artificial intelligence systems, including the following: (i) Cataloging existing artificial intelligence metrics, benchmarks, and evaluation methodologies used in industry and academia. (ii) Testing and validating the efficacy of existing metrics, benchmarks, and evaluations, as well as TEVV tools and products. (iii) Funding and facilitating research and other activities in a transparent manner, including at institutions of higher education and other nonprofit and private sector partners, to evaluate, develop, or improve TEVV capabilities, with rigorous scientific merit, for artificial intelligence systems. (iv) Evaluating foundation models for their potential effect in downstream systems, such as when retrained or fine-tuned. (H) Coordinating with counterpart institutions of international partners and allies to promote global interoperability in the development of research, evaluation, testing, and standards relating to artificial intelligence. (I) Developing tools, methodologies, best practices, and voluntary guidelines for identifying vulnerabilities in foundation models. (J) Developing tools, methodologies, best practices, and voluntary guidelines for relevant agencies to track incidents resulting in harm caused by artificial intelligence systems. (2) Implementation The following functions relating to implementation: (A) Using publicly available and voluntarily provided information, conducting evaluations to assess the impacts of artificial intelligence