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This research demonstrates the practical application of agentic AI in formalizing complex security policies, specifically by correcting and verifying epistemic logic frameworks within a Rocq proof assistant. By leveraging AI to resolve longstanding ambiguities in information flow semantics, the study highlights how machine intelligence can accelerate rigorous validation in cryptography and programming languages. The work underscores a growing trend where AI acts as an essential tool for advancing foundational computer science theory rather than just serving end-user applications.
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Assuming You Knew: Fixing an Epistemic Semantics for Flow Policies Using Agentic AI

arXiv2 min read

arXiv:2608.00882v1 Announce Type: new Abstract: Many high-level security requirements are about the allowed flow of information in programs and are difficult to make precise because they involve selective downgrading. Notions from epistemic logic have emerged as a good approach to policy semantics but a robust general framework remains elusive. A paper appearing in CSF 2018, entitled ``Assuming You Know: Epistemic Semantics of Relational Annotations for Expressive Flow Policies'', attempted to provide a unifying framework---but the formalization was sketchy and a correction was announced during the conference presentation. With aid from an agentic AI coding assistant, a corrected formalization has been machine checked in the Rocq proof assistant. The simplicity and generality of the framework may help compare different policy specification styles and enforce them by leveraging existing techniques.

Abstract:Many high-level security requirements are about the allowed flow of information in programs and are difficult to make precise because they involve selective downgrading. Notions from epistemic logic have emerged as a good approach to policy semantics but a robust general framework remains elusive. A paper appearing in CSF 2018, entitled ``Assuming You Know: Epistemic Semantics of Relational Annotations for Expressive Flow Policies'', attempted to provide a unifying framework---but the formalization was sketchy and a correction was announced during the conference presentation. With aid from an agentic AI coding assistant, a corrected formalization has been machine checked in the Rocq proof assistant. The simplicity and generality of the framework may help compare different policy specification styles and enforce them by leveraging existing techniques.

Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR); Logic in Computer Science (cs.LO); Programming Languages (cs.PL)

arXiv:2608.00882 [cs.AI]

(or arXiv:2608.00882v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2608.00882 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 229 words

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