TL;DR
SHA-256 cannot be broken. No shortcut for mining exists. But proving that produced 7 novel findings.
Setup
- 60 independent experiments
- 19 mathematical frameworks
- 5,000–1,000,000 hash evaluations per experiment
- All signals Bonferroni-corrected and scale-verified (real signals scale as √N)
The 7 Novel Findings
1. Double-SHA-256 is NOT two independent hashes (9.56σ)
Bitcoin's SHA-256d has measurable cross-hash anti-correlation. W[8-15] in the second hash is ALWAYS constant padding — only 30 unique carry patterns exist vs theoretical 2^64.
Not exploitable (r=0.03), but real and never documented.
2. |HW(a)-16| → leading zeros: 20.48σ
The strongest signal in 60 experiments. Absolute deviation of working variable 'a' Hamming weight from 16 predicts output quality at 20.48σ. Invisible to standard linear analysis. Post-computation only.
3. Round 8 is the "insulator" — 17× drop
R0-2: 100% deterministic
R3: carry breaks control (→22%)
R4: nonce enters
R6-7: 26 trackable channels
R8: 💥 ALL 26 destroyed — 17× drop in ONE round
R16-64: perfect white noise
This is WHY every neural net, every evolutionary algorithm, every ML approach fails.
4. Nonce identity preserved (26.25σ) — but useless
Nonce tracking survives all 64 rounds. But nonce→quality correlation = 0.84σ (noise).
Count ⊥ Position. Two completely orthogonal channels.
5. Mixing: 85% linear + 15% nonlinear
- Ch, Maj: <1% contribution each
- ADD carries: 13%
- Rotations Σ0, Σ1: 85%
Ch/Maj = algebraic protection. Rotations = actual mixer.
6. First algebraic mining impossibility proof via Z3
Nonces [0..31] proven IMPOSSIBLE for LZ≥8 at 4-round SHA-256. Algebraically, not probabilistically.
7. Groebner basis: 2^71 worse than brute force
64-round Groebner: ~2^103. Mining brute force: 2^32. The "just solve the polynomial equations" approach is 2 billion billion billion times harder.
All 19 Frameworks — 0 Exploitable Signals
Statistics, Neural Networks, Evolutionary, Spectral, Z3/SAT, Control Theory, FEM, Information Theory, Higher-Order Differentials, Cube Attack, Rebound, ANF, Multi-Variable, Side-Channel, Wang Differentials, p-adic, Tropical Geometry, Groebner, Representation Theory.
Links
- Paper: IACR ePrint 2026/109079
- Code: Zenodo DOI 10.5281/zenodo.19789234 — 60 Python scripts, free
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