securitydatacompliancedraft
2026-01-08Proprietary Data Exposure in AI Systems
Working draft outlining how proprietary data can leak through AI systems, with mitigation ideas for enterprise use.
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Working papers and methodology notes from MLNavigator. These are early lab materials and may change as the work matures.
verificationofflinecryptographydraft
2025-11-12Offline Inference Verification: A Hash-Chain Approach
Draft note on a hash-chain approach for verifying inference runs in air-gapped environments. We describe a proposed artifact format and signing protocol, with early prototype measurements in progress.
Read note →energymeasurementapple-silicondraft
2025-09-20Joules Per Token: An Energy Measurement Methodology for Apple Silicon
Draft methodology note outlining how we measure inference energy on Apple silicon using macOS powermetrics. The protocol is intended for repeatable internal benchmarking; tooling and results are still in development.
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