Containment Verification: AI Safety Guarantees Independent of Alignment

Fuente: arXiv
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Main Authors: Moon, Royce, Varshney, Lav R.
Format: Preprint
Published: 2026
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author Moon, Royce
Varshney, Lav R.
author_facet Moon, Royce
Varshney, Lav R.
contents Agentic frameworks are the software layer through which AI agents act in the world. Existing safety methods intervene on the model and therefore remain conditional on unverifiable properties of learned behavior. We introduce containment verification, which locates safety guarantees in the agentic framework itself. Under havoc oracle semantics, the AI is modeled as an unconstrained oracle ranging over the entire typed action space, and the verified containment layer must enforce the boundary policy for every possible AI output. For boundary-enforceable properties, expressed over modeled boundary events, action arguments, and state, we prove a universal guarantee by forward-simulation refinement and mechanize it in Dafny. We instantiate the paradigm by verifying PocketFlow, a minimalist agentic LLM framework, and use an agentic synthesis pipeline to generate the specification, operational model, and refinement proof under an information barrier against tautological specifications. To our knowledge, this is the first deductive formal verification of an agentic framework, and its guarantee is invariant to model capability over the modeled typed action boundary.
format Preprint
id arxiv_https___arxiv_org_abs_2605_09045
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Containment Verification: AI Safety Guarantees Independent of Alignment
Moon, Royce
Varshney, Lav R.
Artificial Intelligence
Cryptography and Security
Software Engineering
Agentic frameworks are the software layer through which AI agents act in the world. Existing safety methods intervene on the model and therefore remain conditional on unverifiable properties of learned behavior. We introduce containment verification, which locates safety guarantees in the agentic framework itself. Under havoc oracle semantics, the AI is modeled as an unconstrained oracle ranging over the entire typed action space, and the verified containment layer must enforce the boundary policy for every possible AI output. For boundary-enforceable properties, expressed over modeled boundary events, action arguments, and state, we prove a universal guarantee by forward-simulation refinement and mechanize it in Dafny. We instantiate the paradigm by verifying PocketFlow, a minimalist agentic LLM framework, and use an agentic synthesis pipeline to generate the specification, operational model, and refinement proof under an information barrier against tautological specifications. To our knowledge, this is the first deductive formal verification of an agentic framework, and its guarantee is invariant to model capability over the modeled typed action boundary.
title Containment Verification: AI Safety Guarantees Independent of Alignment
topic Artificial Intelligence
Cryptography and Security
Software Engineering
url https://arxiv.org/abs/2605.09045