Provably Secure Agent Guardrail

Fuente: arXiv
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Autori principali: Wu, Benlong, Zhang, Weiming, Chen, Kejiang, Fang, Han, Yu, Nenghai
Natura: Preprint
Pubblicazione: 2026
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author Wu, Benlong
Zhang, Weiming
Chen, Kejiang
Fang, Han
Yu, Nenghai
author_facet Wu, Benlong
Zhang, Weiming
Chen, Kejiang
Fang, Han
Yu, Nenghai
contents As large language models transition from bounded generative engines to agents with expansive execution privileges, AI going out of control precipitates a fundamental crisis in artificial intelligence security. Existing defense architectures heavily rely on empirical semantic guardrails and probabilistic large model adjudicators, mechanisms that fail to provide deterministic security lower bounds when facing complex semantic symbol decoupling attacks. To overcome this empirical semantic guardrail dilemma, this paper proposes a new security paradigm for agents based on the fundamental limitations of logical reasoning. Based on this paradigm, we further introduce an executable Proof-Constrained Action (ePCA) framework with a neural symbolic isolation architecture. This framework abandons semantic trust in natural language, forcing agents to losslessly formalize their intentions into first-order logical mathematical constraints before performing physical operations. Empirical evaluations of macroscopic and microscopic two-dimensional dynamic adversarial systems demonstrate that our formal verification mechanism achieves zero attack success rate and zero false positive rate across the evaluated scenarios, with extremely low computational latency. This research provides a conditional formal foundation under explicit system assumptions and an engineering paradigm for constructing the underlying defense foundation for future intelligent systems.
format Preprint
id arxiv_https___arxiv_org_abs_2605_29251
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Provably Secure Agent Guardrail
Wu, Benlong
Zhang, Weiming
Chen, Kejiang
Fang, Han
Yu, Nenghai
Artificial Intelligence
Cryptography and Security
As large language models transition from bounded generative engines to agents with expansive execution privileges, AI going out of control precipitates a fundamental crisis in artificial intelligence security. Existing defense architectures heavily rely on empirical semantic guardrails and probabilistic large model adjudicators, mechanisms that fail to provide deterministic security lower bounds when facing complex semantic symbol decoupling attacks. To overcome this empirical semantic guardrail dilemma, this paper proposes a new security paradigm for agents based on the fundamental limitations of logical reasoning. Based on this paradigm, we further introduce an executable Proof-Constrained Action (ePCA) framework with a neural symbolic isolation architecture. This framework abandons semantic trust in natural language, forcing agents to losslessly formalize their intentions into first-order logical mathematical constraints before performing physical operations. Empirical evaluations of macroscopic and microscopic two-dimensional dynamic adversarial systems demonstrate that our formal verification mechanism achieves zero attack success rate and zero false positive rate across the evaluated scenarios, with extremely low computational latency. This research provides a conditional formal foundation under explicit system assumptions and an engineering paradigm for constructing the underlying defense foundation for future intelligent systems.
title Provably Secure Agent Guardrail
topic Artificial Intelligence
Cryptography and Security
url https://arxiv.org/abs/2605.29251