sbb-zoo/checkpoints

The trained models of the SNN Backdoor Benchmark, a benchmark for backdoor attacks and defenses on spiking neural networks with neuromorphic data. The leaderboard shows the results they produced.

Most of these models are backdoored on purpose. They exist to reproduce and study the benchmark. Do not deploy them.

Layout

Each artifact is a folder <benchmark version>/<key>/. The key is the hash of everything that determines the artifact, and each result in the benchmark repository names its artifacts by key:

"artifacts": {"clean_model": "8098...", "model": "3174...", "defended_model": "c19d..."}

A model folder holds model.safetensors and checkpoint.json (the architecture, input shape, number of classes and sha256 of the weights). Some also hold trigger.safetensors (a learned trigger) or defense.safetensors (state a defense adds to the model). Detection defenses store their verdict as JSON. There is no pickle file.

Use

git clone https://github.com/GorkaAbad/SNN-Backdoor-Benchmark && cd SNN-Backdoor-Benchmark
uv sync
uv run sbb zoo pull 0.9.0 --revision <commit>   # copies the models into the local cache
uv run sbb reproduce results/0.9.0/<key>.json   # reruns a cell on the published models

Pin a commit with --revision to reproduce a result exactly.

License

The code and these weights are released under the MIT License. The models were trained on N-MNIST, DVS128 Gesture and CIFAR10-DVS, which keep their own licenses. Each attack and defense card in the benchmark repository cites its paper.