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Capability Safety as Datalog: A Foundational Equivalence

Cosimo Spera

Abstract

We prove that capability safety admits an exact representation as propositional Datalog evaluation (Datalogprop: the monadic, ground, function-free fragment of first-order logic), enabling the transfer of algorithmic and structural results unavailable in the native formulation. This addresses two structural limitations of the capability hypergraph framework of Spera [2026]: the absence of efficient incremental maintenance, and the absence of a decision procedure for audit surface containment. The equivalence is tight: capability hypergraphs correspond to exactly this fragment, no more.

Capability Safety as Datalog: A Foundational Equivalence

Abstract

We prove that capability safety admits an exact representation as propositional Datalog evaluation (Datalogprop: the monadic, ground, function-free fragment of first-order logic), enabling the transfer of algorithmic and structural results unavailable in the native formulation. This addresses two structural limitations of the capability hypergraph framework of Spera [2026]: the absence of efficient incremental maintenance, and the absence of a decision procedure for audit surface containment. The equivalence is tight: capability hypergraphs correspond to exactly this fragment, no more.

Paper Structure

This paper contains 43 sections, 11 theorems, 22 equations.

Key Result

Theorem 4.3

Let $H=(V,\mathcal{F})$ be a capability hypergraph and $A\subseteq V$. Under Definition def:encoding-cap-dl:

Theorems & Definitions (38)

  • Definition 3.1: Capability Hypergraph
  • Definition 3.2: Closure Operator
  • Definition 3.3: Safe Region and Minimal Unsafe Antichain
  • Definition 3.4: Emergent Capabilities and Near-Miss Frontier
  • Definition 3.5: Safe Audit Surface
  • Definition 3.6: Propositional Datalog Program
  • Definition 3.7: Datalog Query and Minimal Witness
  • Definition 4.1: The $\text{CapHyp}\to\text{Datalog}_{\mathsf{prop}}$ Encoding
  • Remark 4.2: Stratified Negation
  • Theorem 4.3: Encoding Correctness: $\text{CapHyp}\to\text{Datalog}_{\mathsf{prop}}$
  • ...and 28 more