AI Security Architecture
Secure-by-design architecture for enterprise AI systems — standards, threat models, control baselines, and a practical adoption roadmap.
- Covers LLM, RAG, agentic, and ML pipeline deployment patterns
- Threat modeling mapped to enforceable mitigations with clear ownership
- Evaluation criteria for runtime protection, guardrails, and CI/CD security tooling
The Challenge
Beneath the surface of most generative applications, fundamental security perimeters are missing. Over-scoped IAM roles, unvalidated execution pipelines, and fragile prompt filters cannot substitute for structurally isolated trust boundaries.
Standard cloud security controls fail to map against AI-specific threat models like MITRE ATLAS (Adversarial Threat Landscape for AI Systems) and the OWASP Top 10 for LLM Applications (2025).
Our Approach
We map specific threat models to enforced runtime mitigations, using the NIST AI Risk Management Framework (AI RMF 1.0), CSA MAESTRO (AI Security Assessment Framework), and TARA-AI as structured architectural inputs.
Our blueprints produce deterministic security evidence, guaranteeing that platform safeguards remain intact across complex CI/CD deployments.
Key Outcomes
Core Deliverables
Threat Model and Risk Analysis
A practical AI threat model across data flows, retrieval, tools, identities, models, and operational touchpoints—mapped to enforceable mitigations and ownership boundaries.
- Threat taxonomies: MITRE ATLAS and OWASP LLM Top 10 for injection, leakage, unsafe tool actions, and privilege escalation
- Assessment methodologies: structured analysis using CSA MAESTRO and TARA-AI to define risk boundaries
International energy group
Renewables and grids division
The Context
Security leadership explicitly blocked the deployment of a flagship natural language search tool, citing unresolved risks surrounding unverified document retrieval and broad identity permissions. Teams were paralyzed between intense operational pressure to launch and uncompromising security mandates.
The Outcome
We implemented a structurally sound defense model built on rigid data contracts, dynamic access control, and strict evaluation thresholds. The resulting architecture became the official global standard, safely unblocking AI rollout for a workforce of 12,000 active users.