The computation engine and canonical fixtures for the Cryptographic Concentration Framework (CCF), v1.0-RC. Every canonical figure in the published documents comes from this engine, and this kit reproduces every one of them.
compute_ccf.py– the reference implementation: the Cryptographic Concentration Index over exclusive executing units, band assignment with boundaries closed on the left and Highly concentrated at 4,900 per Universal C.4, failure-domain reach with evidenced and bounded states, and the FS.7 correspondent-banking worked example behind--fs-example.ccf-test-vectors-v1.0rc.md– the ten canonical vectors, human-readable, with the reasoning each vector exists to pin.test-vectors.json– the same ten vectors as machine-readable fixtures.
python3 compute_ccf.py # regenerates the ten vectors and the JSON
python3 compute_ccf.py --fs-example # prints the FS.7 worked-example figures
No dependencies beyond the Python 3 standard library.
The vectors files are script-generated and never hand-edited. Any change goes into the engine and regenerates them – the same rule the framework documents follow. Any implementation that reproduces all ten fixtures is conformant.
The end-to-end reference run joins this kit in September 2026, per the public roadmap. When a date there moves, the change is recorded with the old date and the reason.
This kit, code and fixtures alike, is Apache-2.0. LICENSE and NOTICE are included, and compute_ccf.py has the SPDX identifier at its top. The framework documents at ccframework.org are CC BY 4.0. Neither licence reads onto the other.
The Applied Quantum Cryptographic Concentration Framework, Universal v1.0-RC, Steve Vaile and Marin Ivezic / Applied Quantum, ccframework.org.
CCFramework.org | CBOMProfile.org | PQCFramework.org | AppliedQuantum.com