Guardrails for generative AI
so secrets stay secret.
Guardrails for generative AI
so secrets stay secret.
Guardrails for generative AI
so secrets stay secret.
Guardrails for generative AI
so secrets stay secret.
We are on the precipice of a Cognitive Security Revolution. Network security defends the wires. Cognitive security defends the thoughts flowing through them. We see a future where defense programs, Fortune-500 labs, and fast-moving startups can unleash generative AI without leaking classified data, trade secrets, or sacrifice public trust—uniting national-security rigor with commercial creativity under one protective shield.
Harvard Kennedy School
Master in Public Policy
Artificial Intelligence
Regulatory Compliance
U.S. Army
Cyberwarfare Officer
United States Military Academy
Artificial Intelligence
Mathematics
Computer Science
David brings a decade of national security and cyber operations experience to the private sector. A graduate of West Point and a former Army Officer specializing in cyberwarfare, he has led teams defending against advanced threats in both domestic and overseas assignments. He is currently cond
Scan source code, notebooks, and cloud storage for hardcoded credentials, misconfigured secrets, and unsafe patterns—before they become breaches.
Detect subtle prompt injection risks, LLM misuse, and unauthorized capability exposure using AI-native threat models.
Map technical risks to compliance frameworks like SOC 2, HIPAA, and NIST 800-53. Prioritize issues based on legal exposure, not just CVSS.
Deploy lightweight middleware to enforce policy boundaries for APIs, containers, or LLM endpoints—without rewriting your backend.
Write your own detectors, policies, and safe defaults. Integrate via CLI, API, or IDE plugins for real-time developer feedback.
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