🛡️ Patronus Protect

An on-device AI firewall. It watches the AI traffic going in and out of your apps — browsers, IDEs, native apps, MCP servers — and blocks what shouldn't get through: prompt injections, leaked secrets, shadow AI. Everything runs locally, nothing is sent to a cloud, and it works with any provider (Claude, OpenAI, Gemini, Copilot, Ollama, …).

Patronus Ark

Patronus Ark is the scanning engine underneath the app: a Rust core with Python bindings that scans in three escalating layers, so most traffic is resolved before a transformer ever runs.

Across those layers it catches prompt injection and jailbreaks, PII, secrets and DLP leaks, sensitive documents, risky agentic tool use and MCP policy violations, plus routing and threat classification — all on the endpoint.

Ark will be open source (dual license available). It is not public yet — the repository link will appear here at launch.

The models 🤗

Our detectors, trained for the firewall and shared openly — use them, fine-tune them, benchmark against them, and tell us where they fall short:

• 🐺 Wolf Defender — prompt-injection detection and threat classification (EN/DE)
• 🫍 Orca Sonar — document classification for DLP and sensitive-document routing
• 🦁 Lion Warden — one unified seven-head AI-security model
• 🐕 Husky (Sight / Paw / Nose) — agentic tool use: tool type, operation, data-flow risk
• 🐆 Panther Read — user-intent and request routing
• 🦈 Shark Scent — PII detection
• GLiNER Edge — quantized zero-shot entity extraction (upstream GLiNER, Apache-2.0)

Deliberately small: ModernBERT under the hood, ONNX-quantized (INT8/INT4), a few hundred MB of RAM — they run happily on a laptop instead of a GPU rack.

The app, with downloads for macOS and Windows, lives at patronus.studio. Come say hi.