[FEATURE] Explore blockchain/public ledger integration for metadata verification

[erik-sv]

Problem Statement

There’s currently no decentralized or third-party-verifiable method for validating the authenticity of EncypherAI-signed content (or any AI content whatsoever). While HMAC and local verification are effective for many cases, high-stakes environments like publishing, journalism, compliance-heavy industries, or legal systems may require an immutable, public record.

I’m often frustrated when there’s no standardized way to prove, to any third party, that AI-generated content is legitimate, especially across platforms or long after generation.

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Proposed Solution

Introduce an optional blockchain or decentralized ledger integration to publicly register the metadata or hash of AI-generated text at the moment of creation.

This feature would:

• Allow developers or platforms to “register” metadata or signature hashes to a public chain (e.g., Ethereum, Solana, Hedera, etc.)
• Let third parties verify timestamp, origin, and model source via on-chain verification
• Be fully optional and coexist with local/hosted verification
• Provide CLI/Python interface like:
  • encypher register --public-ledger
  • encypher verify --use-ledger

Components Affected:

• cli/ – new register and verify commands
• core/signing.py – optional output of on-chain transaction hash
• New ledger/ module to handle chain interactions (likely via web3.py or similar)

Impact on existing functionality:

• None if not used — would be opt-in
• Enhances public auditability and trust without requiring centralized servers

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Alternative Solutions

• Rely entirely on hosted verification services or federated registries
• Extend metadata to include signed webhooks to third-party providers
• Use append-only hosted logs with hash-based checkpoints (e.g., Merkle trees), but these lack the decentralization of public chains

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Use Cases

1. Media companies can register all articles created with LLM assistance, proving editorial transparency
2. Education platforms can validate that AI tutors or assignments are generated under authorized workflows
3. Compliance teams can trace when AI-generated financial documents or disclosures were created and by whom
4. Social media platforms could verify content authenticity on-chain when reviewing flagged user posts

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Implementation Ideas

• Chain Options: Ethereum mainnet (costly), L2 like Polygon or Base, or alternative networks like Hedera (low-fee, carbon neutral)
• Data Stored: Hash of metadata or signature, timestamp, and optional signature from publishing party
• Smart Contract: Minimal design — append hash, emit event
• Verification: Fetch via JSON-RPC and compare hash/signature
• CLI Option: Allow --public-ledger flag in encoding and verifying steps
• Privacy: Explore Zero Knowledge proofs or partial hash obfuscation for sensitive fields

Challenges:

• Avoiding high gas costs
• Choosing a reliable, long-term chain
• Maintaining performance and UX simplicity

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Additional Context

This would complement EncypherAI’s “proof at the source” approach by adding decentralized verifiability. Especially useful as content regulation (e.g., EU AI Act) pushes platforms toward transparency and public accountability.

If you’ve worked on similar projects (e.g., web3 notarization, timestamping, DID), we’d love your feedback or collaboration.