Instructions to use hacnho/tensorrt-detectionlayer-nan-score-bypass-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use hacnho/tensorrt-detectionlayer-nan-score-bypass-poc with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
TensorRT DetectionLayer NaN score_threshold bypass proof of concept
This repository contains a bounded research PoC for TensorRT (.engine / .trt / .mytrtfile).
The security question is whether a serialized DetectionLayer_TRT payload can
bypass the creator-side score_threshold >= 0 check by carrying NaN, while
the final built engine still loads and executes normally and silently
suppresses detections.
Files
control.enginenan-score.engineverify_remote_poc.py
What the files demonstrate
Control:
positive_cls -> [0.5]
mixed_bbox -> [0.11951626092195511]
Malicious serialized score_threshold = NaN:
positive_cls -> [0.0]
mixed_bbox -> [0.0]
Verify the public HF artifacts
After unauthenticated download, run:
python verify_remote_poc.py
Expected result:
- both engines deserialize successfully
- both engines execute successfully
- the
nan-score.engineoutput differs from the control on normal presets semantic_suppression_observedistrue
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