Tamper-evident audit trail for AI coding agent activity
SHA-256 hash chains and SMT proofs make AI agent logs actually verifiable.
Rootsign is an open-source tamper-evident decision and action provenance logging library for AI agents
Cryptographic hash chains make agent action logs legally defensible—LangSmith and Langfuse don't do this.
Developers deploying AI agents in regulated industries requiring compliance audit trails
LangSmith · Langfuse · Arize Phoenix
What it does: - SHA-256 hash chain across every Action record in a session - Human-in-the-loop checkpoints with Approval records for certain agent actions - PII redacted before hashing (StandardPIIConfig out of the box) - Works with LangGraph and CrewAI — AutoGen coming soon - Local first (Postgres + Timescale) — no cloud dependency
What it doesn't do (yet): compliance dashboard, cloud backend, policy engine, all on the roadmap.
Please try it out on the Github repo, contributions and feedback are always welcome.
SHA-256 hash chains and SMT proofs make AI agent logs actually verifiable.
Merkle Mountain Range ledger proves AI agents can't retroactively fake logs—novel crypto primitive.
Cryptographic proof audit logs can't be rewritten, even by DB admins.
SHA-256 chained audit logs with embeddable activity feed for customer trust.
Cryptographic audit chain for agents, but lacks observability dashboards competing tools provide.
Instead of another observability dashboard, this project builds a provable audit trail: an OpenAI-compatible reverse proxy that vaults prompts in MinIO and links calls with an HMAC-SHA256 tamper-evident chain, plus replay tooling (replayctl) and Jaeger traces. The cryptographic audit chain and the one-line SDK wrap are clever and practical; the real operational work left to teams will be key management and storage/retention strategy.