tibet-jawbreaker 0.1.1

Provenance-first crypto transactions — every transfer has intent, every wallet has identity

tibet-jawbreaker

Provenance-first crypto transactions — every transfer has intent, every wallet has identity.

Part of the TIBET Protocol stack.

The Problem

Blockchain transactions are anonymous by default. This enables:

• Blind mining — rewards without context or accountability
• Wash trading — A sends to B, B sends back to A
• Intent-free transfers — 50 ETH moved with zero explanation

The chain records what happened. Nobody records why.

The Solution

Jawbreaker adds a TIBET provenance layer to every crypto transaction:

• ERIN (what): amount, from, to, type
• ERAAN (linked to): previous transaction in chain
• EROMHEEN (context): chain, gas, block, exchange rate
• ERACHTER (intent): WHY this transaction exists

No intent? Your legitimacy score drops. It's not forbidden — but it's noticed.

Quick Start

pip install tibet-jawbreaker
tibet-jawbreaker demo

Python API

from tibet_jawbreaker import Ledger, LegitimacyLevel

ledger = Ledger()

# Register wallets with identity
jasper = ledger.register_wallet("jis:jasper", verified=True)
ledger.add_address("jis:jasper", "0x1a2b3c...", "ethereum")

# Transfer WITH intent = legitimate
tx = ledger.transfer(
    from_jis="jis:jasper",
    to_jis="jis:humotica",
    amount=5.0,
    currency="ETH",
    intent="Payment for Q1 development",
    reference="INV-2026-042",
)
print(tx.legitimacy)  # LegitimacyLevel.LEGITIMATE

# Transfer WITHOUT intent = suspicious
tx2 = ledger.transfer(
    from_jis="jis:anon:someone",
    to_jis="jis:anon:other",
    amount=50.0,
    currency="ETH",
)
print(tx2.legitimacy)  # LegitimacyLevel.SUSPICIOUS
print(tx2.flags)       # ['no_intent', 'no_category', 'both_anonymous']

Features

Legitimacy Scoring

Every transaction gets a score (0.0 - 1.0) based on:

• Has intent? (+0.3)
• Has category? (+0.1)
• Has reference? (+0.1)
• Both parties identified? (+0.2)
• Has exchange rate context? (+0.1)

Suspicious Pattern Detection

• Self-transfer: A sends to A (wash trading signal)
• Round-trip: A sends to B, B sends same amount back
• Rapid-fire: Too many transactions from same wallet in short time
• Blind mining: Rewards without context or pool identification

Notary Attestation

Third-party co-signing for extra trust:

attestation = ledger.notarize(
    tx_id=tx.tx_id,
    notary_jis="jis:notary:legal-dept",
    verdict="valid",
    confidence=0.95,
    reason="Invoice verified against contract",
)

Wallet Trust Scores

Trust evolves based on transaction history:

• Legitimacy ratio (60%)
• Verification status (20%)
• History depth (20%)

leaderboard = ledger.leaderboard()

Legitimacy Levels

Level	Score	Meaning
VERIFIED	0.8+	Notary-verified, both parties identified
LEGITIMATE	0.6+	Has intent, identified parties
PLAUSIBLE	0.4+	Has intent but weak identity
UNKNOWN	0.2+	No intent, no context
SUSPICIOUS	0.1+	Pattern matches fraud/laundering
FLAGGED	<0.1	Multiple red flags

Transaction Types

TRANSFER, SWAP, STAKE, UNSTAKE, MINT, BURN, CONTRACT, BRIDGE, REWARD, FEE, PURCHASE, INCOME

License

MIT — Humotica AI Lab 2025-2026

Credits

Designed by Jasper van de Meent. Built by Jasper and Root AI as part of HumoticaOS.

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Stack-positie: Groep specialized · Eigen tijdlijn — niet onderdeel van de ainternet/evidence-spine · ← tibet-ledger · See STACK.md · See demo/golden-path/ for the spine end-to-end.

Enterprise

For private hub hosting, SLA support, custom integrations, or compliance guidance:

Enterprise	[e-mail]
Support	[e-mail]
Security	[e-mail]

See ENTERPRISE.md for details.