2024 · Preprint
CEBin: A Cost-Effective Framework for Large-Scale Binary Code Similarity Detection
CEBin combines code embeddings to shortlist candidate functions with pairwise comparison to detect similar binary code, including vulnerable functions.
Scope and limitations
The paper evaluates CEBin on three binary code similarity datasets and a large-scale benchmark for 1-day vulnerability detection. It reports finding similar functions among millions of candidates in seconds, with 85.46% recall on the vulnerability task.
Why it fits this collection
It studies large-scale binary code similarity detection and its use in finding functions similar to vulnerable code.
Publication and review details
- Venue
- arXiv
- Status
- Preprint
- Publication / posting date
- February 29, 2024
- Date source
- First arXiv submission date.
- First arXiv submission
- February 29, 2024
- arXiv
- 2402.18818
- Reviewed arXiv version
- v1
The date and venue come from the arXiv record.
Sources reviewed
Reviewed against the paper and its primary sources. Cite the original authors using the linked paper or BibTeX.