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Secure Software Development Practices for Generative AI and Dual-Use Foundation Models: An SSDF Community Profile

Published

Author(s)

Harold Booth, Murugiah Souppaya, Apostol Vassilev, Michael Ogata, Martin Stanley, Karen Scarfone

Abstract

This document augments the secure software development practices and tasks defined in Secure Software Development Framework (SSDF) version 1.1 by adding practices, tasks, recommendations, considerations, notes, and informative references that are specific to AI model development throughout the software development life cycle. These additions are documented in the form of an SSDF Community Profile to support Executive Order (EO) 14110, Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, which tasked NIST with "developing a companion resource to the [SSDF] to incorporate secure development practices for generative AI and for dual-use foundation models." This Community Profile is intended to be useful to the producers of AI models, the producers of AI systems that use those models, and the acquirers of those AI systems. This Profile should be used in conjunction with NIST Special Publication (SP) 800-218, Secure Software Development Framework (SSDF) Version 1.1: Recommendations for Mitigating the Risk of Software Vulnerabilities.
Citation
Special Publication (NIST SP) - 800-218A
Report Number
800-218A

Keywords

artificial intelligence, artificial intelligence model, cybersecurity risk management, generative artificial intelligence, secure software development, Secure Software Development Framework (SSDF), software acquisition, software development, software security.

Citation

Booth, H. , Souppaya, M. , Vassilev, A. , Ogata, M. , Stanley, M. and Scarfone, K. (2024), Secure Software Development Practices for Generative AI and Dual-Use Foundation Models: An SSDF Community Profile, Special Publication (NIST SP), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.SP.800-218A, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=958391 (Accessed December 10, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created July 26, 2024