Code for the "ReSIM: Re-ranking Binary Similarity Embeddings to Improve Function Search Performance" paper
To build the docker image using the provided Dockerfile run
docker build -t resafe-img .
Then start a container using the script:
./run_container.sh
We provide the pool extracted from BinCorp as well as pre-computed embeddings for the CLAP model. To run the function search experiments, use the script:
launch_experiments.py
setting the appropriate configuration settings in config.yaml
To reproduce the tables and plots of the paper using pre-computed results, use the notebook
reproduce_results.ipynb
and decompress the .tar.zst archives of BinCorp, MultiComp and BinPool datasets.
Resources for running the experiments as well as the fine-tuned reSIM model are available here