Crawdad is a small security program that runs on your machine. It sits between your AI agents and the upstream LLMs and inspects every request through a multi-layer detection pipeline before it's forwarded. Metadata-only telemetry (event counts, categories, verdicts) egresses by default — raw content never does. Raw prompts, responses, and action parameters stay on your machine by default — enforced by a sanitization chokepoint in the architecture, not policy. Telemetry depth is customer-governed.
Catches direct and indirect injection before the LLM sees the request.
Scans outbound responses for API keys, secrets, internal URLs, and 15 PII categories.
Every decision recorded locally in a SHA-256 Merkle-chained, Ed25519-signed audit trail.
Cmd+Space, type "Terminal", press Enter./usr/local/bin/crawdad-sidecar and registers a LaunchAgent that starts automatically at login.http://localhost:7750. Click Run Test Battery to verify the detection pipeline.Apple Silicon (ARM64) ships full ML detection — the sidecar downloads the model and libonnxruntime in the background after install, then activates on the next restart. Reproducible score: 99.80% detection / 0.09% FP (1/1,172) on the open 497-attack / 1,172-negative benchmark. Intel Macs run pattern-only because upstream ONNX Runtime has no 1.24+ x86_64-apple-darwin wheel. Full notes at Getting Started.
sudo once to register the systemd user unit at /etc/systemd/system/crawdad-sidecar.service.http://localhost:7750. Click Run Test Battery to verify detection.Linux x86_64 and Linux ARM64 both ship full ML detection — the sidecar auto-fetches the platform-specific libonnxruntime 1.24.4 tarball along with the model on first run, then activates ML on the next restart. Reproducible score: 99.80% detection / 0.09% FP (1/1,172) on the open 497-attack / 1,172-negative benchmark.
Or download the signed binary directly:
Windows is not yet supported as a native target and is tracked for a future release.
The recommended path for Windows users is WSL (Windows Subsystem for Linux), which runs the full Linux binary with ML detection:
Open the local dashboard at http://localhost:7750 to see every request inspected, per-layer decisions, and the continuous red team trend. Or see the cloud dashboard for fleet and billing views.