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Cryptoscope: Analyzing cryptographic usages in modern software
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The advent of quantum computing poses a significant challenge as it has the potential to break certain cryptographic algorithms, necessitating a proactive approach to identify and modernize cryptographic code. Identifying these cryptographic elements in existing code is only the first step. It is crucial not only to identify quantum vulnerable algorithms but also to detect vulnerabilities and incorrect crypto usages, to prioritize, report, monitor as well as remediate and modernize code bases. A U.S. government memorandum require agencies to begin their transition to PQC (Post Quantum Cryptograpy) by conducting a prioritized inventory of cryptographic systems including software and hardware systems. In this paper we describe our code scanning tool - Cryptoscope - which leverages cryptographic domain knowledge as well as compiler techniques to statically parse and analyze source code. By analyzing control and data flow the tool is able to build an extendable and querriable inventory of cryptography. Cryptoscope goes beyond identifying disconnected cryptographic APIs and instead provides the user with an inventory of cryptographic assets - containing comprehensive views of the cryptographic operations implemented. We show that for more than 92% of our test cases, these views include the cryptographic operation itself, APIs, as well as the related material such as keys, nonces, random sources etc. Lastly, building on top of this inventory, our tool is able to detect and report all the cryptographic related weaknesses and vulnerabilities (11 out of 15) in CamBench - achieving state-of-the-art performance.
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Hidden Ciphers and Where to Find Them: Static Discovery and Assessment of Cryptographic Assets in Software
A classification-driven static scanner with a separate rule repository discovers and assesses cryptographic assets at rest, achieving F1 0.75 on a synthetic benchmark and finding 370 assets in ten real services.
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