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ZENODO
Preprint . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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airlock: AI Trust as a Variable - A Cryptographic Protocol for Runtime Identity Verification

Authors: Popivanova, Anna;

airlock: AI Trust as a Variable - A Cryptographic Protocol for Runtime Identity Verification

Abstract

Every cryptographic primitive built since 1976 assumes that trust is a constant. AI agents make trust a variable. This paper introduces airlock, a cryptographic zero-trust protocol for runtime identity verification of AI agents, and argues that AI-induced oscillating trust - where an agent's reliability flips rapidly due to stochastic outputs, adversarial prompts, or emergent behaviours - constitutes a fundamental break in the assumptions underlying all existing security primitives. We formalise this as the oscillating trust problem: trust is no longer a binary state verified once and held constant, but a continuous time-series variable demanding new cryptographic primitives. We introduce Invocation-Bound Capability Tokens, agent fingerprinting via static and dynamic traits, environment attestation, emoprinting as affective behavioural continuity verification, and a trust graph governance model. We further demonstrate that existing approaches, including OAuth-based delegation and per-invocation attestation protocols, operate at human-task speed and do not address the inference-speed verification problem that emerges at scale in multi-agent deployments. The protocol is specified across eight RFCs and is available at github.com/popivanova/airlock, with an initial draft committed October 2025.

Keywords

zero trust, runtime verification, agent identity, Cryptographic protocols, oscillating trust, AI Security, AI agents, emoprinting

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green