Datalog Disassembly
Not on the map. Why?
Abstract (arXiv)
Disassembly is fundamental to binary analysis and rewriting. We present a novel disassembly technique that takes a stripped binary and produces reassembleable assembly code. The resulting assembly code has accurate symbolic information, providing cross-references for analysis and to enable adjustment of code and data pointers to accommodate rewriting. Our technique features multiple static analyses and heuristics in a combined Datalog implementation. We argue that Datalog's inference process is particularly well suited for disassembly and the required analyses. Our implementation and experiments support this claim. We have implemented our approach into an open-source tool called Ddisasm. In extensive experiments in which we rewrite thousands of x64 binaries we find Ddisasm is both faster and more accurate than the current state-of-the-art binary reassembling tool, Ramblr.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Jun 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 2; 2023: 2; 2024: 0; 2025: 1; 2026: 2.
7 papers.
- 2023SLaDe: A Portable Small Language Model Decompiler for Optimized Assemblycited by 28
- 2023Boosting Neural Networks to Decompile Optimized Binariescited by 11
- 2022Decompiling x86 Deep Neural Network Executablescited by 7
- 2025Tady: A Neural Disassembler without Structural Constraint Violationscited by 2
- 2022Marvolo: Programmatic Data Augmentation for Practical ML-Driven Malware Detectioncited by 1
- 2026Echo: Learning-based Matching Decompilation using Trusted Back Translationcited by 0
- 2026XLOG: A CUDA-Native Engine for Neurosymbolic Integrationcited by 0
- 2026XLOG: A CUDA-Native Engine for Neurosymbolic Integration23 Sep 2026
- 2026Echo: Learning-based Matching Decompilation using Trusted Back Translation16 Sep 2026
- 2025Tady: A Neural Disassembler without Structural Constraint Violations16 Jun 2025
- 2023SLaDe: A Portable Small Language Model Decompiler for Optimized Assembly21 May 2023
- 2023Boosting Neural Networks to Decompile Optimized Binaries3 Jan 2023
- 2022Decompiling x86 Deep Neural Network Executables3 Oct 2022
- 2022Marvolo: Programmatic Data Augmentation for Practical ML-Driven Malware Detection7 Jun 2022