Using AI to chart a course for our post-quantum migration
Cloudflare built CryptoLabe, an AI-powered internal tool that maps classical cryptography across its codebase to drive its 2029 post-quantum migration.
Cloudflare details CryptoLabe, an internal AI-powered tool that discovers and classifies cryptography usage across its centralized codebase to support its 2029 full post-quantum readiness deadline. The tool runs two-stage scans over source, configuration, manifests, lockfiles, scripts, tests, and documentation, using models to follow evidence across files and enrich findings with internal documentation and ticketing systems. It addresses the limits of grep-based discovery, which overcounts unused code and misses defaults, indirect dependencies, and usage context like JWT versus TLS or SSH. CryptoLabe remains internal, but Cloudflare is publishing its methodology so other organizations can apply it to their own migrations.
- CryptoLabe uses LLMs to map crypto usage beyond naive grep
- Two-stage scans cover source, config, lockfiles, tests, and docs
- Targets Cloudflare's 2029 full post-quantum readiness deadline
- Tool stays internal; methodology shared for other organizations
From the original article
14 min read at blog.cloudflare.com
We’re building CryptoLabe, an internal AI-powered tool that discovers cryptography across our codebase, surfaces dependencies, and helps us progress toward a full post-quantum migration by 2029. Here’s what we’ve learned so far.
By Sharon Goldberg · blog.cloudflare.com
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