Tamper‑evident decision records for AI, anchored to RFC 3161

说明与用途

tg‑attest 为高风险 AI 系统提供防篡改的决策日志，将每个证据集锚定到 RFC 3161 TSA，并使用 Merkle 链证明完整性。

问题

High‑risk AI systems must log decisions with evidence that is tamper‑evident and admissible as evidence, but existing LLM observability tools only record that a document was retrieved, not its content at the time of decision.

结果

tg‑attest enables high‑risk AI systems to produce tamper‑evident, verifiable decision records that satisfy EU AI Act logging requirements, reducing audit data transfer to ~8 KB per record and allowing auditors to independently verify evidence integrity with standard tools.

工作流

• 1. Capture decision data and all evidence items at decision time.
• 2. Compute a hash for each evidence item and store the content.
• 3. Build a Merkle tree over the evidence hashes and compute the epoch root.
• 4. Batch epoch roots into a Merkle epoch and generate a Merkle inclusion proof for each evidence item.
• 5. Submit the epoch root to an RFC 3161 TSA to obtain a signed timestamp token.
• 6. Store the decision record JSON, Merkle proofs, and TSA token in a repository.
• 7. To verify, fetch the TSA token, verify the signature with the TSA’s CA certificate, check the Merkle inclusion proof, and confirm the epoch root matches the stored hash.

证据

tg‑attest records the point‑in‑time state of every piece of evidence a decision consumed, hashes each record into a chain, batches them into Merkle epochs, and anchors the epoch root to an RFC 3161 timestamp authority.

来源

The Merkle layer isn’t gold plating. A regulator asks about one loan. Without inclusion proofs you hand over the whole ledger to answer. With them you hand over 8 KB.

来源

An auditor verifies with a CA certificate they fetch themselves, not one I supply. The timestamp checks out with stock openssl and nothing installed.

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