Black-Box to Gray-Box Uplift

Black-box observation captures what a system reveals at the surface: inputs, outputs, and the behavior that can be inferred without privileged access. That evidence is useful, but it leaves internal preconditions unresolved and often forces risk judgments to remain broad or tentative. Gray-box context adds the missing qualifiers: architecture and data paths, identity and authority relationships, runtime traces and configuration, and control or approval state. The result is not a replacement for the original attack engine, but a better-qualified assessment that binds observed behavior to supported preconditions and converts ambiguity into a bounded transition sequence with evidence-linked consequence. This comparison shows how system context upgrades a raw behavioral signal into a structured return object that is more actionable, more defensible, and more precise.