Govern AI with Evidence.
Independent research on AI governance, regulatory obligations, risk controls, and assurance practices.
AI Governance Framework Map
A structured view of how AI regulations, management-system standards, risk frameworks, and assurance practices relate to one another.
Research Outputs
Security-led research on AI governance, regulatory compliance, risk controls, and assurance evidence for organizations developing, deploying, or using AI systems.
AI SECURITY & RISK
AI Security and
Risk Controls
Research on AI threats, data exposure, model misuse, system vulnerabilities, and practical security controls across the AI lifecycle.
GOVERNANCE & COMPLIANCE
Regulatory and
Standards Mapping
Practical mapping of the EU AI Act, Korea AI Basic Act, ISO/IEC 42001, NIST AI RMF, and related requirements.
CONTROL & ASSURANCE
Controls, Evidence,
and Assurance
Connecting compliance requirements to control owners, implementation records, testing procedures, monitoring, and reviewable evidence.
GyunAI Methodology
Security-Led Analysis
We assess AI systems, data flows, identities, integrations, and attack surfaces to identify technical and operational risks.
Compliance Mapping
We map applicable regulations and standards to governance responsibilities, policies, lifecycle processes, and security controls.
Evidence-Based Assurance
We validate control design and operation through testing, monitoring, logs, implementation records, and reviewable evidence.
Featured Research
AI Security and Risk Controls
A practical analysis of threats, data exposure, model misuse, application vulnerabilities, and security controls across the AI lifecycle.
Security-Led AI Compliance
Mapping AI regulations and standards to governance responsibilities, technical controls, testing activities, and reviewable assurance evidence.
Latest Insights
JULY 31, 2026 / SECURITY BRIEF
AI Security and Risk Controls
A practical overview of threats, sensitive data exposure, model misuse, application vulnerabilities, and security controls across the AI lifecycle.
COMING SOON / COMPLIANCE NOTE
Security-Led AI Compliance
How organizations can map AI regulations and standards to governance responsibilities, technical controls, and operational processes.
COMING SOON / ASSURANCE GUIDE
Evidence for AI Governance
A structured approach to control ownership, implementation records, testing, monitoring, and reviewable assurance evidence.
Research Principles
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Security-Led Compliance
Evidence Before Claims
Regulation Is Not Guidance
Controls Must Be Testable
Collaborate with the Lab
Interested in our governance methodology or looking to discuss a partnership? Reach out to our research team below.
Independent Analysis, Delivered.
Subscribe for security-led analysis, regulatory interpretation, and original perspectives on AI governance, cyber risk, compliance, and assurance.