Human-Certified Module Repositories for the AI Age

TL;DR

This paper introduces Human-Certified Module Repositories (HCMRs), a new framework for creating trustworthy, curated, and provenance-rich software modules to ensure reliability in AI-assisted development.

Contribution

It proposes the HCMRs framework combining human oversight and automated analysis for certifying modules and supporting safe assembly in AI-driven software workflows.

Findings

HCMRs provide a structured approach for module certification and provenance tracking.

Analysis of threat surfaces highlights risks in modular ecosystems.

Lessons from recent failures inform the HCMRs design and governance.

Abstract

Human-Certified Module Repositories (HCMRs) are introduced in this work as a new architectural model for constructing trustworthy software in the era of AI-assisted development. As large language models increasingly participate in code generation, configuration synthesis, and multi-component integration, the reliability of AI-assembled systems will depend critically on the trustworthiness of the building blocks they use. Today's software supply-chain incidents and modular development ecosystems highlight the risks of relying on components with unclear provenance, insufficient review, or unpredictable composition behavior. We argue that future AI-driven development workflows require repositories of reusable modules that are curated, security-reviewed, provenance-rich, and equipped with explicit interface contracts. To this end, we propose HCMRs, a framework that blends human oversight with automated analysis to certify modules and support safe, predictable assembly by both humans and AI agents. We present a reference architecture for HCMRs, outline a certification and provenance workflow, analyze threat surfaces relevant to modular ecosystems, and extract lessons from recent failures. We further discuss implications for governance, scalability, and AI accountability, positioning HCMRs as a foundational substrate for reliable and auditable AI-constructed software systems.