A Dataset of Parametric Cryptographic Misuses
Cryptographic APIs (Crypto APIs) provide the foundations for the development of secure applications. Unfortunately, most applications do not use Crypto APIs securely and end up being insecure, e.g., by the usage of an outdated algorithm, a constant initialization vector, or an inappropriate hashing algorithm. Two different studies [1], [2] have recently shown that 88% to 95% of those applications using Crypto APIs are insecure due to misuses. To facilitate further research on these kinds of misuses, we created a collection of 201 misuses found in real-world applications along with a classification of those misuses. In the provided dataset, each misuse consists of the corresponding open-source project, the project’s build information, a description of the misuse, and the misuse’s location. Further, we integrated our dataset into MUBench [3], a benchmark for API misuse detection. Our dataset provides a foundation for research on Crypto API misuses. For example, it can be used to evaluate the precision and recall of detection tools, as a foundation for studies related to Crypto API misuses, or as a training set.
- M. Egele, D. Brumley, Y. Fratantonio, and C. Kruegel, “An Empirical Study of Cryptographic Misuse in Android Applications,” in Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security, ser. CCS ’13. New York, NY, USA: ACM, 2013, pp. 73–84.
- S. Krüger, J. Späth, K. Ali, E. Bodden, and M. Mezini, “CrySL: An Extensible Approach to Validating the Correct Usage of Cryptographic APIs,” p. 27, 2018.
- S. Amann, S. Nadi, H. A. Nguyen, T. N. Nguyen, and M. Mezini, “MUBench: a benchmark for API-misuse detectors,” in Proceedings of the 13th International Workshop on Mining Software Repositories - MSR ’16. Austin, Texas: ACM Press, 2016, pp. 464–467.
Mon 27 MayDisplayed time zone: Eastern Time (US & Canada) change
09:40 - 10:30 | Session IV: SecurityMSR 2019 Data Showcase / MSR 2019 Technical Papers at Centre-Ville Chair(s): Sarah Nadi University of Alberta | ||
09:40 15mFull-paper | Automated Software Vulnerability Assessment with Concept Drift MSR 2019 Technical Papers | ||
09:55 6mTalk | A Manually-Curated Dataset of Fixes to Vulnerabilities of Open-Source Software MSR 2019 Data Showcase | ||
10:01 15mFull-paper | Negative Results on Mining Crypto-API Usage Rules in Android Apps MSR 2019 Technical Papers Jun Gao University of Luxembourg, SnT, Pingfan Kong Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Li Li Monash University, Australia, Tegawendé F. Bissyandé SnT, University of Luxembourg, Jacques Klein University of Luxembourg, SnT | ||
10:16 6mTalk | A Dataset of Parametric Cryptographic Misuses MSR 2019 Data Showcase Anna-Katharina Wickert TU Darmstadt, Germany, Michael Reif TU Darmstadt, Germany, Michael Eichberg TU Darmstadt, Germany, Anam Dodhy , Mira Mezini TU Darmstadt, Germany Link to publication DOI Pre-print Media Attached | ||
10:22 6mTalk | RmvDroid: Towards A Reliable Android Malware Dataset with App Metadata MSR 2019 Data Showcase Haoyu Wang Beijing University of Posts and Telecommunications, China, Junjun Si , Hao Li , Yao Guo Peking University |