draft-sharif-agent-audit-trail
Agent Audit Trail: A Standard Logging Format for Autonomous AI Systems
This document specifies a standard logging format for autonomous
AI agent systems. The Agent Audit Trail (AAT) defines a
JSON-based record structure with mandatory fields for agent
identity, action classification, outcome tracking, and trust
level reporting. Records are linked via tamper-evident hash
chaining using SHA-256 per RFC 8785, with optional ECDSA
signatures for non-repudiation.
The format addresses requirements from the EU AI Act
(Regulation 2024/1689), which mandates automatic recording of
events for high-risk AI systems effective August 2026. It also
maps to SOC 2 Trust Services Criteria, ISO/IEC 42001, and
PCI DSS v4.0.1 logging requirements.
The design is transport-agnostic and supports export to JSONL,
Syslog (RFC 5424), and CSV while preserving chain integrity.
Privacy is addressed through input/output hashing and tombstone-
based deletion compatible with GDPR Article 17.