Evaluating Crypto Misuses in Python: Insights from GitHub Projects and MicroPython

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Evaluating Crypto Misuses in Python: Insights from GitHub Projects and MicroPython
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Learn about definite misuses, dependency impacts, rule violations, and insights into security vulnerabilities across cryptographic libraries.

Authors: Anna-Katharina Wickert, Technische Universität Darmstadt, Darmstadt, Germany ; Lars Baumgärtner, Technische Universität Darmstadt, Darmstadt, Germany ; Florian Breitfelder, Technische Universität Darmstadt, Darmstadt, Germany ; Mira Mezini, Technische Universität Darmstadt, Darmstadt, Germany . Table of Links Abstract and 1 Introduction 2 Background 3 Design and Implementation of Licma and 3.1 Design 3.2 Implementation 4 Methodology and 4.

is definitely violated by the respective API call. We identified 85 definite misuses which could be identified within one class file and thus are local. The remaining 1,416 misuses are potential misuses. 5.1.1 Dependencies. From the 1,501 misuses, only 7.00 % are within the application code and not in dependencies. These misuses are within 14.81 % of the applications with at least one misuse. The remaining misuses are found in dependencies and can be reduced to 290 unique misuses.

As discussed in Section 3.1, we distinguish between potential and definite misuses. While a potential misuse requires a manual inspection to decide whether it is harmful, a definite misuse indicates that the analysis was able to resolve the respective crypto parameter. Thus, we know that a rule of

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