Shellcode_IA32: A Dataset for Automatic Shellcode Generation
arXiv:2104.13100 · doi:10.18653/v1/2021.nlp4prog-1.7
Abstract
We take the first step to address the task of automatically generating shellcodes, i.e., small pieces of code used as a payload in the exploitation of a software vulnerability, starting from natural language comments. We assemble and release a novel dataset (Shellcode_IA32), consisting of challenging but common assembly instructions with their natural language descriptions. We experiment with standard methods in neural machine translation (NMT) to establish baseline performance levels on this task.
Paper accepted to NLP4Prog Workshop 2021 co-located with ACL-IJCNLP 2021. Extended journal version of this work has been published in the Automated Software Engineering journal, Volume 29, Article no. 30, March 2022, DOI: 10.1007/s10515-022-00331-3