AWS
Security operating patterns for IAM, organizations, data boundaries, detection, Bedrock, and agentic application control.
- IAM roles, STS, Organizations, SCPs
- CloudTrail, Config, Security Hub, GuardDuty
- KMS, VPC endpoints, Macie, Lake Formation
Cloud
Security patterns for AWS, GCP, Azure, and AI control planes
Training and implementation work is organized around the provider controls and AI runtime boundaries teams actually operate.
GCP
Practical control design for service accounts, Workload Identity Federation, VPC Service Controls, Vertex AI, and evidence export.
- Service account lifecycle and keyless access
- Cloud Asset Inventory and Audit Logs
- Sensitive Data Protection and VPC Service Controls
Azure
Security training and implementation paths for Entra ID, Azure Policy, Defender, Purview, Private Link, and Azure OpenAI.
- Managed identities and federated credentials
- Azure Policy, Resource Graph, Defender for Cloud
- Key Vault, Private Link, Purview
AI Platforms
Controls for LLM applications, retrieval, model supply chain, evaluation pipelines, and runtime mediation.
- Prompt injection and output validation
- Model provenance and AIBOM practices
- Eval-gated deployment and drift response
Agentic Systems
A control-plane view of agents: identity, tool gateways, memory, action approval, traceability, and kill switches.
- MCP and tool metadata assurance
- Least-privilege action scoping
- Runtime traces and circuit breakers
Governance & Assurance
Evidence-driven governance that maps technical controls to standards, exceptions, release decisions, and audit packs.
- NIST AI RMF and ISO/IEC 42001 mapping
- Gate evidence and exception records
- Dashboards for drift and remediation
Need a provider-specific path?
Bring the cloud account structure, AI workload, or training objective. We will map it to controls, labs, gate evidence, and an implementation backlog.