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FoC: Figure out the Cryptographic Functions in Stripped Binaries with LLMs

FoC: Figure out the Cryptographic Functions in Stripped Binaries with LLMs

27 March 2024
Guoqiang Chen
Xiuwei Shang
Shaoyin Cheng
Yanming Zhang
Weiming Zhang
Neng H. Yu
N. Yu
ArXivPDFHTML

Papers citing "FoC: Figure out the Cryptographic Functions in Stripped Binaries with LLMs"

5 / 5 papers shown
Title
Trim My View: An LLM-Based Code Query System for Module Retrieval in Robotic Firmware
Sima Arasteh
Pegah Jandaghi
Nicolaas Weideman
Dennis Perepech
Mukund Raghothaman
Christophe Hauser
Luis Garcia
65
0
0
05 Mar 2025
Extending Source Code Pre-Trained Language Models to Summarise
  Decompiled Binaries
Extending Source Code Pre-Trained Language Models to Summarise Decompiled Binaries
Ali Al-Kaswan
Toufique Ahmed
M. Izadi
A. Sawant
Prem Devanbu
A. van Deursen
SyDa
66
30
0
04 Jan 2023
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
301
11,730
0
04 Mar 2022
A Systematic Evaluation of Large Language Models of Code
A Systematic Evaluation of Large Language Models of Code
Frank F. Xu
Uri Alon
Graham Neubig
Vincent J. Hellendoorn
ELM
ALM
188
624
0
26 Feb 2022
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for
  Code Understanding and Generation
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
Yue Wang
Weishi Wang
Shafiq R. Joty
S. Hoi
199
1,451
0
02 Sep 2021
1