Using AI to chart a course for our post-quantum migration
Blog post from Cloudflare
Cloudflare aims to achieve full post-quantum cryptographic readiness by 2029, extending its existing post-quantum TLS encryption deployments to authentication, legacy connections, and other public-key systems. To manage the scale and complexity of identifying cryptography across numerous repositories, configurations, dependencies, and protocols, it is developing CryptoLabe, an internal AI-assisted tool that discovers cryptographic uses, analyzes their runtime context, classifies classical and post-quantum implementations, tracks migration metrics, and identifies shared prerequisites or difficult cases. Built on Cloudflare’s Developer Platform using Workers, Durable Objects, Workflows, R2, D1, AI Gateway, Workers AI, and isolated Sandboxes, CryptoLabe uses staged scans and engineering review to produce actionable reports for product managers and developers while avoiding unsupported conclusions. Cloudflare emphasizes that post-quantum migration depends on standards, libraries, vendors, clients, and other ecosystem participants, and recommends that other organizations prioritize their most sensitive or exposed systems, apply broad protective controls where available, validate findings with system owners, and address high-impact upgrades and common blockers before attempting exhaustive cryptographic inventories.
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