mlsanityData to 14 Oct 2026

Shellcode_IA32: A Dataset for Automatic Shellcode Generation

arXiv 2104.13100 ↗First posted 27 Apr 2021cs.SE cs.CLcited by 16

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 34 of its 97 references that are in the map. First posted on arXiv 27 Apr 2021.

Builds on

34 of 97 references.

References · 34

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  4. 2020Language Models are Few-Shot Learnerscited by 32,419
  5. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  6. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,548
  7. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,057
  8. 2014Sequence to Sequence Learning with Neural Networkscited by 2,986
  9. 2018Deep contextualized word representationscited by 2,290
  10. 2016Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translationcited by 1,475
  11. 2020CodeBERT: A Pre-Trained Model for Programming and Natural Languagescited by 1,310
  12. 2015Effective Approaches to Attention-based Neural Machine Translationcited by 1,026
22 more
  1. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 687
  2. 2019CodeSearchNet Challenge: Evaluating the State of Semantic Code Searchcited by 654
  3. 2017A Structured Self-attentive Sentence Embeddingcited by 318
  4. 2018code2seq: Generating Sequences from Structured Representations of Codecited by 179
  5. 2018Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflowcited by 165
  6. 2018Coarse-to-Fine Decoding for Neural Semantic Parsingcited by 110
  7. 2018NL2Bash: A Corpus and Semantic Parser for Natural Language Interface to the Linux Operating Systemcited by 98
  8. 2017Structured Attention Networkscited by 95
  9. 2017Abstract Syntax Networks for Code Generation and Semantic Parsingcited by 92
  10. 2018TRANX: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generationcited by 88
  11. 2016Latent Predictor Networks for Code Generationcited by 73
  12. 2019On Learning Meaningful Code Changes via Neural Machine Translationcited by 50
  13. 2019Does BLEU Score Work for Code Migration?cited by 49
  14. 2017Automatically Generating Commit Messages from Diffs using Neural Machine Translationcited by 42
  15. 2017From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihoodcited by 41
  16. 2018Retrieval-Based Neural Code Generationcited by 41
  17. 2020Incorporating External Knowledge through Pre-training for Natural Language to Code Generationcited by 36
  18. 2016Simpler Context-Dependent Logical Forms via Model Projectionscited by 33
  19. 2020TF-Coder: Program Synthesis for Tensor Manipulationscited by 27
  20. 2018XNMT: The eXtensible Neural Machine Translation Toolkitcited by 14
  21. 2018Learning to Generate Corrective Patches using Neural Machine Translationcited by 10
  22. 2020Relevance Transformer: Generating Concise Code Snippets with Relevance Feedbackcited by 6

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 7; 2023: 3; 2024: 3; 2025: 2; 2026: 1.

16 papers.

Sort:

By area:

  1. 2024LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Codecited by 2,004
  2. 2022Recent Advances in Neural Text Generation: A Task-Agnostic Surveycited by 14
  3. 2022Who Evaluates the Evaluators? On Automatic Metrics for Assessing AI-based Offensive Code Generatorscited by 11
  4. 2022BashExplainer: Retrieval-Augmented Bash Code Comment Generation based on Fine-tuned CodeBERTcited by 9
  5. 2023Automating the Correctness Assessment of AI-generated Code for Security Contextscited by 6
  6. 2022CodexDB: Generating Code for Processing SQL Queries using GPT-3 Codexcited by 5
  7. 2023Neuron Patching: Semantic-based Neuron-level Language Model Repair for Code Generationcited by 5
  8. 2022CORNET: Learning Table Formatting Rules By Examplecited by 4
  9. 2025Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Qualitycited by 4
  10. 2022A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspectivecited by 3
  11. 2023Enhancing Robustness of AI Offensive Code Generators via Data Augmentationcited by 3
  12. 2024Enhancing AI-based Generation of Software Exploits with Contextual Informationcited by 3
4 more
  1. 2022Can NMT Understand Me? Towards Perturbation-based Evaluation of NMT Models for Code Generationcited by 2
  2. 2024Optimizing AI-Assisted Code Generationcited by 2
  3. 2025A Semantic-based Optimization Approach for Repairing LLMs: Case Study on Code Generationcited by 2
  4. 2026Willing but Unable: Separating Refusal from Capability in Code LLMs via Abliterationcited by 0