mlsanityData to 14 Oct 2026

Agyn: An Open-Source Platform for AI Agents with Scalable On-Demand Execution, Agent Definition as a Code, and Zero-Trust Access

arXiv 2605.27575 ↗First posted 26 May 2026cs.AIcited by 0

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Abstract (arXiv)

As organizations move toward production deployments of AI agents, which execute non-deterministic workflows, maintain stateful sessions, and often operate with privileged access to internal services, the engineering challenge shifts from building individual agents to operating them at scale with proper isolation, governance, and security. In this paper we present Agyn, an open-source platform designed around three key principles tailored for agent workloads: a signal-driven, stateful serverless runtime on Kubernetes; a Terraform provider for agent and harness definition; and a security model grounded in zero-trust and least-privilege principles. Agyn is agent-agnostic, model-agnostic, and cloud-agnostic.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 24 references that are in the map. First posted on arXiv 26 May 2026.

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7 of 24 references.

References · 7

  1. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  2. 2023Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injectioncited by 1,443
  3. 2025Agentic AI Security: Threats, Defenses, Evaluation, and Open Challengescited by 28
  4. 2025A Practical Guide for Designing, Developing, and Deploying Production-Grade Agentic AI Workflowscited by 15
  5. 2018Serverless Computing: One Step Forward, Two Steps Backcited by 12
  6. 2018Where Are The Gaps? A Systematic Mapping Study of Infrastructure as Code Researchcited by 9
  7. 2025Beyond Pipelines: A Survey of the Paradigm Shift toward Model-Native Agentic AIcited by 8

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