AI Security & Governance (ISO 42001)
AI Risk Management & Compliance Framework
End-to-end AI security governance framework design aligned with ISO 42001, NIST AI RMF, EU AI Act, and OWASP Top 10 for LLM. Covers AI asset inventory, risk classification, threat modeling, agentic AI controls, maturity assessment, and policy development.
What's Included
Comprehensive service features designed to meet your security and development needs.
AI Security Framework Design
Comprehensive governance framework covering 12 requirement areas: security governance, risk classification, threat modeling, acceptable use, secure development, deployment controls, data security, monitoring, and incident response.
AI Asset Inventory & Risk Classification
Full lifecycle inventory of all AI systems with risk-based classification. Map AI models, training data sources, third-party AI tools, and shadow AI usage across the organization.
AI Threat Modeling
AI-specific threat modeling covering adversarial attacks, prompt injection, data poisoning, model extraction, distributional shift, and emergent behavior risks. Mapped to MITRE ATLAS tactics.
Agentic AI Security Controls
Security controls for autonomous AI agents: least privilege enforcement, tool access boundaries, multi-agent trust policies, human oversight requirements, and escalation workflows.
AI Security Maturity Assessment
Five-level maturity model evaluating current AI security posture with gap analysis and prioritized improvement roadmap.
Policy & Playbook Development
Actionable AI security policies covering acceptable use, data handling, access control, change management, and incident response. Step-by-step playbooks with checklists for each security control.
Key Benefits
Why organizations choose this service
Establish structured AI governance before regulatory enforcement
Align with ISO 42001, NIST AI RMF, and EU AI Act requirements
Prevent shadow AI deployments and uncontrolled agent access
Reduce AI-specific risks: data poisoning, model theft, prompt injection
Get a clear maturity roadmap with prioritized improvements
Prepare for ISO 42001 certification readiness
AI Security Governance Process
Our proven methodology for delivering ai security & governance (iso 42001)
Discovery & Current State Analysis
Extract AI asset inventory, conduct stakeholder interviews, review existing policies and controls, map third-party AI tools and shadow AI usage, and analyze regulatory requirements applicable to your organization.
AI Asset Inventory & Risk Classification
Build comprehensive inventory of all AI systems including models, data pipelines, APIs, and agent workflows. Classify each by risk level based on autonomy, data sensitivity, business impact, and regulatory exposure.
AI Threat Modeling
Conduct threat modeling for adversarial attacks, prompt injection, data poisoning, model extraction, and agentic AI risks. Map threats to MITRE ATLAS framework and OWASP Top 10 for LLM Applications.
Framework Design & Policy Development
Design 12-requirement-area AI Security Framework. Develop governance policies, acceptable use rules, secure development standards, deployment controls, and data security requirements aligned with ISO 42001 and NIST AI RMF.
Agentic AI Security Controls
Define controls for AI agents: least privilege access, tool authorization policies, multi-agent trust boundaries, human-in-the-loop requirements, output validation, and autonomous action limits.
Maturity Assessment & Gap Analysis
Evaluate current AI security posture against five-level maturity model. Identify gaps, benchmark against industry standards, and validate compliance with EU AI Act, KVKK, GDPR, and sector-specific regulations.
Implementation Roadmap & Handover
Deliver final framework documentation, security control playbooks with checklists, prioritized implementation roadmap, management presentation with risk summary and decision items, and ongoing support guidance.
Technologies We Use
Industries We Secure
Specialized security solutions tailored to your industry