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LastPyMile: identifying the discrepancy between sources and packages.

, , , , and . ESEC/SIGSOFT FSE, page 780-792. ACM, (2021)

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LastPyMile: identifying the discrepancy between sources and packages., , , , and . ESEC/SIGSOFT FSE, page 780-792. ACM, (2021)Typosquatting and Combosquatting Attacks on the Python Ecosystem., , , , and . EuroS&P Workshops, page 509-514. IEEE, (2020)APR4Vul: an empirical study of automatic program repair techniques on real-world Java vulnerabilities., , , , and . Empir. Softw. Eng., 29 (1): 18 (February 2024)HIT4Mal: Hybrid image transformation for malware classification., , , , , and . Trans. Emerg. Telecommun. Technol., (2020)A Convolutional Transformation Network for Malware Classification., , , , , and . CoRR, (2019)A Benchmark Comparison of Python Malware Detection Approaches., , and . CoRR, (2022)Mac-A-Mal: macOS malware analysis framework resistant to anti evasion techniques., , and . J. Comput. Virol. Hacking Tech., 15 (4): 249-257 (2019)py2src: Towards the Automatic (and Reliable) Identification of Sources for PyPI Package.. ASE, page 1394-1396. IEEE, (2021)An efficient neural network model for time series forecasting of malware., , and . J. Intell. Fuzzy Syst., 35 (6): 6089-6100 (2018)On the feasibility of detecting injections in malicious npm packages., , , and . ARES, page 115:1-115:8. ACM, (2022)