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Abstract

Modern software systems rely on cryptography for data protection, authentication, and trust establishment, yet organizations often lack a structured view of the cryptography deployed across source code, configuration, dependencies, and cryptographic files. This lack of visibility complicates security governance and post-quantum migration planning. This paper presents a static approach for discovering and assessing cryptographic assets in software systems. We introduce a classification of Crypto-Material, Crypto-Artifacts, and Crypto-Invocations, derive an extensible scanner-independent rule repository from it, and implement a static scanner that applies these rules to produce CBOM-oriented output. We evaluate the approach on a synthetic benchmark with known ground truth and on a real-world infrastructure of ten deployed services. The scanner achieves an F1 score of 0.75 for asset discovery and correctly annotates 91% of expected weaknesses and vulnerabilities. In the real-world setting, it processes 57 610 files in under six minutes and discovers 370 cryptographic assets, including six CVE-linked vulnerabilities and 52 post-quantum migration candidates. Real-world coverage is assessed against a manually compiled reference list rather than an exhaustive one. These results show that classification-driven static discovery can provide practical cryptographic transparency for governance and post-quantum migration planning.