I analyze complex systems for systemic risk, the kind traditional security frameworks miss. My work focuses on lawful instability: failure modes that emerge when rational actors optimize systems at machine speed using strictly valid behavior. No exploits. No unauthorized access. Just math.
Background
10 years analyzing complex logistic systems and incentive structures (Canadian Pacific Railway, 2010-2020). Lesson learned: catastrophe rarely comes from a bug. It comes from a system working exactly as designed in an unforeseen context.
Independent security research since 2020
Published forensic analyses of blockchain compromises and AI infrastructure vulnerabilities
Developed analytical frameworks for evaluating systemic risk in agentic systems
Active research on adversarial equilibria, identity architecture, and mechanism design
No conflicts of interest
No products to sell. No implementation services to upsell. No vendor relationships. No bug bounty platforms. No security tool affiliations. My only compensation comes from analysis work.
Active research areas
Lawful instability in agentic systems: how AI agents and automated systems exploit gradient surfaces in business logic without violating any rules
Conservation-based security invariants: moving from policy-based security (is this allowed?) to invariant-based security (can the system survive this aggregate behavior?)
Post-incident forensic reconstruction: blockchain compromise analysis and root cause identification using only public data sources