Three-layer mask hypothesis: CT = Mask + Columnar(Vig(PT, key))

In plain English: Three-layer mask hypothesis: CT = Mask + Columnar(Vig(PT, key)) — using a method that writes text into a grid and reads columns in a keyword-determined order (columnar transposition). 161 thousand key/parameter combinations were tested. This approach is ruled out within the tested scope.

NOISE

How to read this record

Verdict – NOISE (no better than random guessing), INTERESTING (slightly above random, almost certainly coincidence), SIGNAL (statistically unusual, warrants investigation), or FULL MATCH (all 24 known letters correct).
Confidence Tier – Tier 1 = mathematical proof (permanent). Tier 2 = every possibility tested. Tier 3 = partially tested. Tier 4 = not yet tested.
Configs Tested – How many different key/parameter combinations were tried.
Best Score – How many of the 24 known plaintext letters the best attempt matched (out of 24).
Keystream Consistency (Bean) – Whether the key values at different positions are mathematically consistent with each other.
Scope Limitations – What this elimination does not rule out.

Configs Tested: 161,280
Best Score: 0 / 24 known letters matched · no better than random guessing (random guess would score: 0.0)
Keystream Consistency (Bean): FAIL
Checks whether the key values at different positions are mathematically consistent with each other.
Confidence: Not classified.
Script: scripts/_uncategorized/e_s_30_three_layer_mask.py

Reproduce

PYTHONPATH=src python3 -u scripts/_uncategorized/e_s_30_three_layer_mask.py

Requires the kryptos repo, Python 3.11+, PYTHONPATH=src.

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