The zero-knowledge tool-gating in week 2 is the piece that actually matters long-term. Regex filtering and a watchdog model are both still betting on catching a bad call after the fact; never putting the secret in context at all removes the failure mode instead of trying to detect it. Good that you framed stages 1 and 2 as "document why this gets bypassed" rather than presenting them as if they were sufficient.
The precision-over-coverage principle in week 3 also deserves to be said more often. A scanner that's right 95% of the time but noisy gets ignored faster than one that's right 60% of the time but only speaks up when it's confident, alert fatigue kills tooling adoption regardless of how technically correct it is.
The sequencing logic ties it together well, each week becomes both a defense and a target for the next, so week 4's red-team runner isn't testing a toy, it's testing infrastructure you already built and can explain at the trust-boundary level.
Sanoary Istiaque
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The MCP security scanner and multi-turn red-team runner ideas are also very relevant as AI agents become more connected to external tools and data sources. These are the kinds of projects that can genuinely help developers build stronger AI systems. Great roadmap for anyone looking to move deeper into AI security.