Toolkit to assess and determine model provenance
AetherGuard AI is presented as a holistic AI Trust & Integrity Gateway that expands the typical AI gateway paradigm to offer real-time semantic inspection, cryptographic accountability, responsible AI compliance, and robust operational governance. The system operates as a transparent reverse-proxy between LLM clients and providers.
Validate model and release claims against small provenance envelopes with redacted output.
Security-grade model lineage and attestations on top of CycloneDX ML-BOM
Anchor W&B artifacts to Bitcoin. Zero-touch provenance for ML experiments.
Supply-chain forensics for AI models. Traces lineage, audits licenses, flags trust gaps.
Static analysis toolchain for neural network weights - inspect, diff, fingerprint, and scan model checkpoints without running them. Ghidra for models.
Anchor MLflow artifacts to Bitcoin. One line to production.
Decentralized, poisoning-resistant distribution for ML models and datasets. Publishers sign once, untrusted mirrors distribute, and any consumer verifies the exact signed bytes with full provenance.
Add a description, image, and links to the model-provenance topic page so that developers can more easily learn about it.
To associate your repository with the model-provenance topic, visit your repo's landing page and select "manage topics."