Spaces:
Running
Running
| title: README | |
| emoji: 📊 | |
| colorFrom: red | |
| colorTo: yellow | |
| sdk: static | |
| pinned: false | |
| license: mit | |
| short_description: 'Security admission and adversarial test corpus for local AI ' | |
| ## LayerFault Security Corpus | |
| The corpus contains deliberately synthetic, malformed and adversarial model repositories designed to reproduce security conditions that defensive tooling should detect. | |
| Coverage includes: | |
| - unsafe Pickle and serialization | |
| - NumPy object arrays | |
| - Safetensors structural anomalies | |
| - PyTorch and TorchScript packages | |
| - Hugging Face custom loaders and `auto_map` | |
| - tokenizer and template attacks | |
| - hidden and Unicode instructions | |
| - Python, PowerShell, JavaScript and shell capability chains | |
| - executable and native library payloads | |
| - archive and path traversal attacks | |
| - suspicious sidecars | |
| - dependency and package integrity anomalies | |
| - malformed model formats | |
| - provenance and lineage mismatches | |
| - synthetic weight anomalies and backdoor fixtures | |
| - dataset poisoning | |
| - runtime security test cases | |
| The corpus is organised into Hugging Face Collections so individual security domains can be explored and tested independently. | |