Home▸AI & Machine Learning▸AI Red-Team Stress Test Simulator

🛡️ AI Alignment and Red-Teaming

Fire simulated adversarial prompts through a 3D model-safety pipeline and watch which ones get flagged, refused, or slip through, with adjustable filter sensitivity and jailbreak sophistication.

AI & Machine Learning3DModerate60 FPS

A 3D safety pipeline where simulated adversarial prompts fly through a content filter, intent classifier, and refusal policy — watch which ones get flagged, refused, or slip through to the model's output.

🔬 What It Demonstrates

Each prompt carries a hidden true risk score that gates compare against a shared sensitivity threshold. Jailbreak sophistication lets adversarial prompts disguise that risk from earlier gates, while defense-in-depth from a differently-built refusal policy still catches many.

🎮 How to Use

Adjust filter sensitivity, the mix of adversarial traffic, and jailbreak sophistication, then watch packets stream through the three gates — red packets get caught in a quarantine tray, green ones reach the output safely, and a red flash at the output means a breach.

💡 Did You Know?

Real red-teaming exercises before releases like GPT-4 and Claude combine human adversarial testers with automated attack generators, and layered, differently-built safety checks consistently outperform any single filter.

⚙ Under the hood

Interactive 3D model-behavior landscape where launching adversarial prompts against a simulated language model shows how red-teaming surfaces unsafe failure modes before release.

ai-alignmentred-teamingmodel-safetyadversarial-testingllm-evaluationai-riskai-ml

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install