Awesome-Info-Inferring-Binary

A collection of papers, tools about type inferring, variable renaming, function name inferring on stripped binary executables.

Papers

Paper	Venue	Year	Slide	Video	Source Code	Dataset
llasm: Naming Functions in Binaries by Fusing Encoder-only and Decoder-only LLMs	TOSEM	2025	S	V	llasm	D
ReSym: Harnessing LLMs to Recover Variable and Data Structure Symbols from Stripped Binaries	CCS	2024	S	V	ReSym	D
TYGR: Type Inference on Stripped Binaries using Graph Neural Networks	Usenix Sec	2024	S	V	TYGR	D
Enhancing Function Name Prediction using Votes-Based Name Tokenization and Multi-task Learning	Proceedings of the ACM on Software EngineeringVolume 1, Issue FSE	2024	S	V	Epitome	D
Ahoy SAILR! There is No Need to DREAM of C: A Compiler-Aware Structuring Algorithm for Binary Decompilation	Usenix Sec	2024	S	V	SAILR	D
"Len or index or count, anything but v1": Predicting Variable Names in Decompilation Output with Transfer Learning	S&P	2024	S	V	VarBERT	D
FunProbe: Probing Functions from Binary Code through Probabilistic Analysis	ESEC/FSE	2023	S	V	FunProbe	D
CFG2VEC: Hierarchical Graph Neural Network for Cross-Architectural Software Reverse Engineering	ICSE	2023	S	V	CFG2VEC	D
A Transformer-based Function Symbol Name Inference Model from an Assembly Language for Binary Reversing	AsiaCCS	2023	S	V	AsmDepictor	D
SymLM: Predicting Function Names in Stripped Binaries via Context-Sensitive Execution-Aware Code Embeddings	CCS	2022	S	V	SymLM	SymLM
DnD: A Cross-Architecture Deep Neural Network Decompiler	Usenix Sec	2022	S	V	DnD	D
DIRECT : A Transformer-based Model for Decompiled Variable Name Recovery	nlp4prog	2021	S	V	DIRECT-nlp4prog	D
XFL: Naming Functions in Binaries with Extreme Multi-label Learning	S&P(Arxiv)	2023(2021)	S	V	XFL	D
Variable Name Recovery in Decompiled Binary Code using Constrained Masked Language Modeling	Arxiv	2021	S	V	G	D
DIRTY: Augmenting Decompiler Output with Learned Variable Names and Types	Usenix Sec	2022	S	V	DIRTY | Demo	D
A Lightweight Framework for Function Name Reassignment Based on Large-Scale Stripped Binaries	ISSTA	2021	S	V	NFRE	D
StateFormer: Fine-Grained Type Recovery from Binaries using Generative State Modeling	ESEC/FSE	2021	S	V	StateFormer	D
OSPREY: Recovery of Variable and Data Structure via Probabilistic Analysis for Stripped Binary	S&P (Oakland)	2021	S	V	OSPREY	D
Devil Is Virtual: Reversing Virtual Inheritance in C++ Binaries	CCS	2020	S	V	G	D
Neural reverse engineering of stripped binaries using augmented control flow graphs	OOPLSA	2020	S	V	Nero	D
CATI: Context-Assisted Type Inference from Stripped Binaries	DSN	2020	S	V	G	D
Typilus: Neural Type Hints	PLDI	2020	S	V	Typilus	D
In Nomine Function: Naming Functions in Stripped Binaries with Neural Networks	Arxiv	2019	S	V	in_nomine_function	D
DIRE: A Neural Approach to Decompiled Identifier Naming	ASE	2019	S	V	Dire	D
Type Learning for Binaries and its Applications	IEEETR	2019	S	V	BITY	D
DeClassifier: Class-Inheritance Inference Engine for Optimized C++ Binaries	AsiaCCS	2019	S	V	DeClassifier	D
DEBIN:Predicting Debug Information in Stripped Binaries	CCS	2018	S	V	DEBIN | debin.ai	D
Meaningful variable names for decompiled code: a machine translation approach	ICPC	2018	S	V	G	D
Neural Nets Can Learn Function Type Signatures From Binaries	Usenix Sec	2017	S	V	EKLAVYA	binary.tar.gz, pickles.tar.gz, clean_pickles.tar.gz
DSIbin: Identifying Dynamic Data Structures in C/C++ Binaries	ASE	2017	S	V	DSIbin	D
A Tough call: Mitigating Advanced Code-Reuse Attacks At The Binary Level	S&P (Oakland)	2016	S	V	TypeArmor	D
Type Inference on Executables	ACMCS	2016	S	V	G	D
Scalable variable and data type detection in a binary rewriter	PLDI	2013	S	V	G	D
TIE: Principled reverse engineering of types in binary programs	NDSS	2011	S	V	G	D
Automatic Reverse Engineering of Data Structures from Binary Execution	NDSS	2010	S	V	G	D

Tools

• 2019 in_nomine_function
• 2019 Dire && New URL && datasets
• 2018 DEBIN && debin.ai
• 2017 EKLAVYA
• 2018 decomp