Datasets:
taisazero
commited on
Commit
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271e5f2
1
Parent(s):
925e19f
updated class name and documentation
Browse files- Shellcode_IA32.py +23 -11
Shellcode_IA32.py
CHANGED
@@ -25,18 +25,30 @@ import datasets
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# TODO: Add BibTeX citation
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# Find for instance the citation on arxiv or on the dataset repo/website
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_CITATION = """\
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@
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title = {A
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author=
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}
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"""
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# TODO: Add description of the dataset here
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# You can copy an official description
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_DESCRIPTION = """\
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"""
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# TODO: Add a link to an official homepage for the dataset here
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@@ -54,7 +66,7 @@ _URLs = {
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# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
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class
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"""Shellcode_IA32 a dataset for shellcode generation"""
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VERSION = datasets.Version("1.1.0")
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@@ -70,10 +82,10 @@ class Shellcode_IA32(datasets.GeneratorBasedBuilder):
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# You will be able to load one or the other configurations in the following list with
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# data = datasets.load_dataset('my_dataset', 'first_domain')
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# data = datasets.load_dataset('my_dataset', 'second_domain')
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BUILDER_CONFIGS = [
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]
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DEFAULT_CONFIG_NAME = "default" # It's not mandatory to have a default configuration. Just use one if it make sense.
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# TODO: Add BibTeX citation
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# Find for instance the citation on arxiv or on the dataset repo/website
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_CITATION = """\
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@inproceedings{liguori-etal-2021-shellcode,
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title = "{S}hellcode{\_}{IA}32: A Dataset for Automatic Shellcode Generation",
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author = "Liguori, Pietro and
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Al-Hossami, Erfan and
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Cotroneo, Domenico and
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Natella, Roberto and
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Cukic, Bojan and
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Shaikh, Samira",
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booktitle = "Proceedings of the 1st Workshop on Natural Language Processing for Programming (NLP4Prog 2021)",
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month = aug,
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year = "2021",
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address = "Online",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2021.nlp4prog-1.7",
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doi = "10.18653/v1/2021.nlp4prog-1.7",
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pages = "58--64",
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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.",
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}
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"""
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# TODO: Add description of the dataset here
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# You can copy an official description
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_DESCRIPTION = """\
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Shellcode_IA32 is a dataset for shellcode generation from English intents. The shellcodes are compilable on Intel Architecture 32-bits.
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"""
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# TODO: Add a link to an official homepage for the dataset here
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# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
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class ShellcodeIA32(datasets.GeneratorBasedBuilder):
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"""Shellcode_IA32 a dataset for shellcode generation"""
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VERSION = datasets.Version("1.1.0")
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# You will be able to load one or the other configurations in the following list with
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# data = datasets.load_dataset('my_dataset', 'first_domain')
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# data = datasets.load_dataset('my_dataset', 'second_domain')
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# BUILDER_CONFIGS = [
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# datasets.BuilderConfig(name="default", version=VERSION, description="This part of my dataset covers the default train/test split"),
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# #datasets.BuilderConfig(name="second_domain", version=VERSION, description="This part of my dataset covers a second domain"),
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# ]
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DEFAULT_CONFIG_NAME = "default" # It's not mandatory to have a default configuration. Just use one if it make sense.
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