AI Audit Logs — Cryptographic Audit Logging for AI Systems
Most AI systems have logs. Few have audit logs. The difference is tamper-evidence, cryptographic integrity, and independent verifiability — not just timestamps in a database.
CertifiedData records every AI system action as a chain-linked, Ed25519-signed audit entry. Any modification to a prior record breaks the chain — making tampering immediately detectable.
Why traditional audit logs fail compliance requirements
Mutable
Standard logs can be edited, deleted, or overwritten. This makes them unsuitable as evidence for regulatory audits.
No integrity proof
Without cryptographic signatures, there is no way to prove a log entry was not modified after the fact.
No artifact linkage
Traditional logs record events in isolation — not linked to the specific dataset or model version that produced the decision.
How CertifiedData implements AI audit logs
Append-only structure
New entries are only ever appended — never modified or deleted. The log grows in one direction. This is enforced at the storage level.
SHA-256 chain hashing
Each entry includes a chain_hash: the SHA-256 hash of the prior entry. This creates a hash-chain where modifying any entry invalidates every subsequent entry — detectable without access to the original system.
Ed25519 signing
Every entry is signed with CertifiedData's Ed25519 private key. The signature is verifiable using the public key at /.well-known/signing-keys.json — no account or API access required.
Dataset linkage
Each audit entry references a certified dataset certificate ID, creating a direct link from the AI decision to the data that produced it — essential for EU AI Act Article 10 data governance.
Standard audit logs vs cryptographic AI audit logs
| Capability | Standard logs | CertifiedData audit logs |
|---|---|---|
| Tamper-evident | ✗ | ✓ chain-linked SHA-256 |
| Cryptographic signature | ✗ | ✓ Ed25519 per entry |
| Independent verification | ✗ | ✓ public key |
| Dataset linkage | ✗ | ✓ certificate ID reference |
| Regulatory grade | Partial | ✓ EU AI Act Art. 12 + 19 |
| Append-only enforcement | Rarely | ✓ structural guarantee |
Frequently asked questions
What are AI audit logs?
AI audit logs are structured records of AI system behavior — decisions made, inputs processed, outputs produced, and policies applied. To be compliance-grade, they must be tamper-evident (append-only, not modifiable), cryptographically verifiable (signed so authenticity can be proven), and traceable (linked to datasets and model versions). Standard application logs do not meet these requirements.
Why are traditional audit logs insufficient for AI compliance?
Traditional logs can be modified, lack cryptographic integrity, and are not linked to AI artifacts like training datasets or model versions. This means they cannot prove that a specific decision was made by a specific model from specific data — exactly what regulators require under the EU AI Act. Cryptographic AI audit logs solve this by signing each entry and linking decisions to certified artifact IDs.
How does CertifiedData implement AI audit logs?
CertifiedData records each decision as a signed log entry containing: decision ID, timestamp, decision label, outcome, model version, certified dataset reference, SHA-256 chain hash linking to the prior entry, and an Ed25519 signature. The append-only structure and chain hashes make the log tamper-evident. The signatures enable independent verification using the public key at /.well-known/signing-keys.json.
What is the difference between AI audit logs and AI decision logs?
AI audit logs and AI decision logs are closely related. Decision logging is the continuous process of recording individual events. An audit log is the structured, ordered collection of those records — the history you hand to an auditor. In CertifiedData, every decision log entry is also part of the audit log, since all entries are chain-linked and preserved in sequence.
Do AI audit logs satisfy EU AI Act Article 12?
EU AI Act Article 12 requires that high-risk AI systems automatically record events — including system inputs, the operation of the system, and significant incidents. CertifiedData audit logs record all three with timestamps, cryptographic signatures, and dataset references. The machine-readable format allows automated compliance verification without manual documentation.