arXiv:2104.13100
공식 코드 · Papers with Code
Shellcode_IA32: A Dataset for Automatic Shellcode Generation
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT
In-Domain African Languages Translation Using LLMs and Multi-armed Bandits
THOR-MoE: Hierarchical Task-Guided and Context-Responsive Routing for Neural Machine Translation
Combining the Best of Both Worlds: A Method for Hybrid NMT and LLM Translation
CoCoNuT: Combining Context-Aware Neural Translation Models using Ensemble for Program Repair
CycleDistill: Bootstrapping Machine Translation using LLMs with Cyclical Distillation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.