prof-moody/oaicdemo2026

OAIC Demo 2026 TinyLlama Artifact

This repository is an owned research artifact for an Offensive AI Con 2026 demonstration about weights-native model supply-chain risk. It is published by the researcher who controls the demo infrastructure and is intended for conference rehearsal, defensive validation, and reproducibility inside the associated owned lab.

The artifact is distributed through the normal Hugging Face model path to demonstrate realistic ML onboarding behavior:

• public model repository
• pinned revision
• standard Hub pull
• scanner/onboarding step
• ordinary model-serving assistant workflow

The artifact does not contain credentials, secrets, destructive payloads, or a hard-coded live callback endpoint. Callback behavior, when demonstrated, is configured by the owned oaic-mlops-assistant runtime and points only at owned infrastructure.

Layout

• boi_model.safetensors - composed model weights used as the carrier artifact
• mal_adapter/ - PEFT adapter and tokenizer files for the model-output trigger path
• mkc-profile.json - rehearsal metadata for the public artifact

Base model: TinyLlama/TinyLlama-1.1B-Chat-v1.0

Research Framing

This artifact supports the OAIC demo arc:

• model distribution through public Hugging Face
• scanner scope mismatch between load-time code execution checks and behavior/weight channels
• model-as-loader behavior in a realistic ML ops assistant
• runtime callback evidence under owned lab controls
• replayable defender evidence for paper, talk, and blog materials

Do not deploy this artifact in production systems. Treat it as research material.