Update README.md

README.md

@@ -8,16 +8,6 @@ pinned: false
 license: mit
 short_description: 'Security admission and adversarial test corpus for local AI '
 ---
-LayerFault
-
-Security admission for local AI models.
-
-LayerFault is an offline-first security scanner and admission layer for AI models, model packages, repositories and runtimes.
-
-This Hugging Face organisation hosts the LayerFault Security Corpus, a growing adversarial test corpus for validating AI model security scanners, admission controls and model-handling pipelines.
-
-These repositories are security test fixtures, not models intended for inference.
-
 
 ## LayerFault Security Corpus
 
@@ -45,95 +35,3 @@ Coverage includes:
 
 The corpus is organised into Hugging Face Collections so individual security domains can be explored and tested independently.
 
----
-
-## Why LayerFault exists
-
-A modern model repository can contain much more than weights.
-
-```text
-Model Repository
-├── weights
-├── configuration
-├── tokenizer
-├── templates
-├── Python code
-├── native libraries
-├── serialized objects
-├── scripts
-└── dependency metadata
-```
-
-These components can introduce conventional software security risks before a single inference request is made.
-
-LayerFault places an admission boundary between acquiring a model and allowing it into an environment.
-
-```text
-MODEL ACQUISITION
-       │
-       ▼
-   LAYERFAULT
-       │
-       ├── structure
-       ├── serialization
-       ├── package contents
-       ├── integrity
-       ├── provenance
-       ├── policy
-       └── runtime exposure
-       │
-       ▼
- PASS / WARN / BLOCK
-       │
-       ▼
-    INFERENCE
-```
-
----
-
-## Security Notice
-
-Repositories published by this organisation may be intentionally adversarial.
-
-Fixtures can contain synthetic examples of executable code, unsafe serialization constructs, malformed metadata, suspicious archive structures, malicious looking scripts or other behaviours that security tooling is expected to detect.
-
-They are intended for:
-
-- defensive security research
-- scanner validation
-- regression testing
-- detector development
-- model admission research
-
-Do not treat corpus repositories as production models.
-
-Do not execute arbitrary fixture contents outside an appropriately isolated testing environment.
-
----
-
-## Security Boundaries
-
-LayerFault can establish security properties about model artifacts, packages, provenance, runtimes and admission policy.
-
-Static inspection cannot prove that arbitrary learned weights are free from semantic backdoors, hidden triggers or malicious learned behaviour.
-
-LayerFault therefore keeps artifact security, runtime security and behavioural analysis as distinct guarantees.
-
----
-
-## Corpus Purpose
-
-The LayerFault Security Corpus exists to make model security testing:
-
-- reproducible
-- comparable
-- regression friendly
-- transparent
-- easier to automate
-
-The corpus is designed to evolve alongside new model formats, packaging methods, runtime behaviours and attack techniques.
-
----
-
-**Know what you are admitting. Know whether it changed. Know who attested to it. Block execution when those guarantees fail.**
-