Technical report / Version 1
Agent Manifest: Portable, Hardware-Attestable Identity and Provenance for AI Agents
OPAQUE Systems
Abstract
Agent Manifest proposes a signed record of the artifacts that define an AI agent, including its system prompt, model, policy, tools, retrieval corpus, memory, decision trace, delegation, supply chain, and human approvals. Artifact digests and canonical serialization make changes to the recorded baseline detectable when a verifier has the relevant artifacts and trusted keys. The design composes SPIFFE identities, RFC 8785 canonicalization, Ed25519 signatures, an optional ML-DSA-65 profile, and hardware-attestation bindings. This technical report describes the original model and preserves the recorded Ed25519 software benchmarks, delegation checks, and tamper probes. Signed metadata alone does not prove that the recorded configuration was used during execution. The evaluation does not measure post-quantum performance or establish live hardware provenance; continuous verification of mutable memory and retrieval state is outside its scope. Current SDK behavior and normative requirements are maintained separately.
What this report contributes
A signed baseline for agent artifacts, with recorded Ed25519 benchmarks, delegation checks, and tamper probes.
Evidence and limits
- The saved benchmark run is dated July 1, 2026, on Windows 11, CPython 3.12.10, and an ARMv8 Qualcomm host.
- Only the Ed25519 profile was measured. The recorded environment did not have the optional post-quantum dependency; no ML-DSA-65 performance result is claimed.
- Signed artifacts do not establish that those artifacts were used during execution. Continuous validation of mutable memory and retrieval state is outside this evaluation.
- The saved environment does not identify the exact SDK commit. It supports inspection of the recorded results, but not a claim of fully pinned independent reproduction.
The source package preserves the recorded inputs and results. No new experiment run or independent replication is claimed for this edition.
Read the current specification and implementation guidance. This report describes an earlier design and evaluation; the current specification governs implementation.
Cite this report
Imran Siddique. Agent Manifest: Portable, Hardware-Attestable Identity and Provenance for AI Agents. AgenTrust technical report, version 1, 2026.
Download BibTeX / Download CITATION.cff
@techreport{agentrust2026agentmanifest,
title = {Agent Manifest: Portable, Hardware-Attestable Identity and Provenance for AI Agents},
author = {Imran Siddique},
institution = {AgenTrust},
year = {2026},
type = {Technical report},
note = {Version 1; not peer reviewed},
doi = {10.5281/zenodo.23001698},
url = {https://agentrust-io.com/research/agent-manifest/v1/}
}
Version history
Version 1, September 27, 2026: Separates signed-baseline checks from proof of runtime use, states evaluation limits, and adds the publication scope and patent notice.
Based on a manuscript originally dated June 23, 2026, with later recorded experiments. That manuscript date is not presented as a verified publication date.
File checksums. Published version files are retained; substantive revisions receive a new version.
Questions and corrections
Open an issue in the project repository and identify the report version and section.