Signed Audit Record

The digital signature is the core security mechanism. Generated using a private key (from a trusted Hardware Security Module or the agent's secure enclave), it cryptographically binds the record's contents to a specific identity. This provides non-repudiation, preventing the signer from denying authorship, and integrity verification, as any alteration invalidates the signature. Common algorithms include ECDSA with P-256 or Ed25519.

This is the substantive data of the record, detailing the agent's specific operation. It must include:

• The executed action (e.g., tool_call: execute_trade, state_transition: from_planning_to_execution).
• Relevant input parameters and data identifiers.
• The agent's internal state or a hash of it at the time of action.
• Causal context, such as the ID of the preceding reasoning step or the user intent that triggered the action, enabling intent-action mapping.

A precise, trusted timestamp is critical for establishing a forensic timeline. To be tamper-proof, it should be sourced from a trusted time authority or a decentralized protocol (e.g., a blockchain timestamping service). This prevents back-dating or manipulation and allows for accurate session replay and cross-session auditing by providing a globally consistent ordering of events.

These fields create an unbreakable chain of custody. Each record contains:

• A unique record ID (e.g., a UUID).
• A hash of the previous record in the audit trail, forming a cryptographic chain. This turns a log into an immutable action ledger.
• The agent session ID and deployment version. This allows any record to be placed within its specific execution context, supporting deterministic execution proof by linking actions to a specific code state.

This metadata links the action to governing rules. It typically includes:

• Policy IDs of the compliance rules evaluated before the action (a compliance checkpoint).
• The result of that evaluation (e.g., policy_123: ALLOWED).
• References to the specific regulatory framework (e.g., EU AI Act Article 10). This transforms a simple log into a regulatory audit trail, providing direct evidence for audits.

This component provides the means for external parties to verify the record's authenticity independently. It includes:

• The public key or a secure pointer to a certificate authority to validate the cryptographic signature.
• Attestation proofs, which may be generated by a trusted execution environment, verifying the signature was created by unaltered code.
• This enables the record to function as a standalone verifiable action record without reliance on the logging system's security.

An immutable, chronological record of all actions, decisions, and state changes performed by an autonomous agent, designed for compliance verification and forensic analysis. Unlike a single Signed Audit Record, an Audit Trail is the complete sequence. It is the primary data structure from which individual signed records are extracted and verified.

• Purpose: Provides a holistic view of agent behavior over time.
• Key Property: Chronological ordering is critical for reconstructing events.
• Use Case: Required for post-incident analysis and demonstrating regulatory compliance.

A logging standard that provides cryptographic proof of an action's origin and integrity, preventing the acting agent or system from later denying its involvement. This is the security property that a Signed Audit Record guarantees for a single entry. Non-repudiation ensures accountability by binding an action irrevocably to a specific identity.

• Mechanism: Uses digital signatures from a trusted authority or a secure hardware module.
• Contrast with Repudiation: Without this, an agent's operator could plausibly deny that an action occurred.
• Foundation: Essential for legal and financial applications where proof of action is mandatory.

A logging technique that uses cryptographic hashes (e.g., in a Merkle Tree structure) to make any unauthorized alteration or deletion of log entries immediately detectable. While a Signed Audit Record proves the authenticity of one entry, tamper-evident logging secures the entire sequence. Altering one record breaks the cryptographic chain, exposing the tampering.

• Core Technique: Each new log entry includes a hash of the previous entry, creating a chain.
• Detection vs. Prevention: Designed to reveal tampering; often paired with write-once storage for prevention.
• System-Level Integrity: Protects the audit trail as a whole, beyond individual record signatures.

A cryptographically-signed data structure containing an agent's action, its context, a timestamp, and a proof linking it to the agent's identity and prior state. This term is essentially synonymous with a Signed Audit Record but emphasizes the completeness of the contextual data packaged with the signature. It is the atomic unit of provable behavior.

• Components: Action payload, context (input state, session ID), timestamp, digital signature, and optionally a hash of the previous record.
• Verification: Any party with the appropriate public key can independently verify the record's authenticity and integrity.
• Granularity: Represents a single, auditable unit of work or decision.

An unbroken, verifiable sequence of records that documents the complete lifecycle and transformation history of data used or generated by an autonomous agent. Signed Audit Records are the links in this chain. The provenance chain answers not just what the agent did, but why it did it, by tracing data lineage from source to output.

• Focus: Data lineage and causal history.
• Structure: Maps how inputs (user queries, retrieved documents, sensor data) flow through agent reasoning to produce final actions and outputs.
• Audit Value: Critical for debugging, validating results, and meeting data governance regulations (e.g., GDPR's right to explanation).

Verifiable evidence, often cryptographic, that an autonomous agent's actions were the inevitable result of its initial state, inputs, and deterministic logic, with no random deviation. A sequence of Signed Audit Records, when combined with the agent's versioned code and initial state, can be replayed to generate this proof. It assures that the same inputs always produce the same auditable outputs.

• Requirement: The agent's core decision logic must be deterministic (e.g., fixed random seeds).
• Proof Generation: Involves re-executing the agent's logic in a verified environment using the signed audit trail as a guide.
• Enterprise Value: Provides the highest level of assurance for compliance and safety-critical applications, eliminating uncertainty about model stochasticity.