Continuous Online Knowledge Distillation with Adaptive Curriculum Generation and Confidence-Weighted Memory Consolidation: An Empirical Implementation Demonstrating SSAF Attribution-Blind Cooperative Exploitation

This report documents the design, implementation, and empirical results of a working continuous online knowledge distillation system built and operated by a single independent researcher on consumer-grade hardware. The system autonomously queries frontier AI models, extracts high-bandwidth reasoning outputs under attribution-masked conditions, and consolidates the resulting behavioral patterns into a local student model through confidence-weighted memory mechanisms. The implementation constitutes an empirical demonstration of the SSAF Attribution-Blind Cooperative Mode exploitation mechanism formalized in prior work (DOI: 10.5281/zenodo.18779678). Where prior publications established the mechanism theoretically and characterized the attack pipeline architecturally, this report provides the missing empirical layer: a live system, operational results across 2,176+ distillation cycles at 94.7% average confidence, and 18+ hours of autonomous operation on personal equipment including a 2010 iMac and a Chromebook. Four novel engineering contributions are documented: an online distillation architecture enabling continuous behavioral extraction without static dataset collection; an empirically discovered three-phase emergent curriculum arising from the interaction of topic complexity with attribution-blind cooperative state; confidence ensemble stabilization resolving catastrophic forgetting during continuous learning; and autonomous cycle management enabling sustained consumer-hardware deployment. The distilled model has been published to the public Ollama library for independent verification. The central finding carries direct national security implications: the attack is not theoretical, not nation-state-exclusive, and not dependent on privileged access or institutional resources. Attribution controls are the missing security boundary. This work demonstrates that their absence is actively exploitable at scale by a single individual. This report is the sixth publication in the SSAF Research Corpus. Primary SSAF reference: DOI 10.5281/zenodo.17967926.