Open Source Intelligence (OSINT) and the fog of war at the strategic level: Defence industrial production in Russia

Abstract The war in Ukraine has increased attention to Open Source Intelligence (OSINT), though most research focuses on tactical use or effects on public opinion. This article asks whether OSINF can be methodically transformed into reliable strategic intelligence under wartime uncertainty. Using Russia’s defence industry as a case study, we compare three production scenarios: official claims, expert estimates, and an Open Source Information–based (OSINF) model derived from shares in battlefield losses. The OSINT scenario shows large discrepancies, suggesting actual output is much lower than reported. We argue that with proper methodological treatment, presented in the paper, OSINF now offers sufficient detail to assess national defence capacity. Our approach demonstrates OSINT’s potential to complement traditional intelligence by introducing a novel methodological framework for cross-validating OSINT-derived data against official claims and expert estimates. The findings engage scholarly debates on the integration of OSINT with conventional frameworks by providing a replicable and transparent model for producing more accurate strategic assessments, even at the strategic level.