Hands-on delivery across
Azure security & engineering
Every engagement is implementation-led. Architecture decisions are codified, controls are deployed, and your team gets the documentation to operate what's been built. All services are aligned to NIST CSF 2.0, NCSC CAF, CIA Triad, and relevant NIST 800-53 / AI RMF controls.
Azure Security Architecture
Design and deploy enterprise-grade Zero Trust architectures on Azure. From secure landing zone blueprints and hub-and-spoke network topologies through to identity hardening, privileged access, and data protection — aligned to CIS benchmarks and NIST 800-53 controls.
- Zero Trust architecture design and implementation
- Azure secure landing zones and subscription governance
- Entra ID configuration — MFA, SSPR, identity lifecycle
- Conditional Access policies and named location controls
- PIM/PAM — just-in-time privileged access governance
- B2B federation and external identity management
- Network segmentation — NSGs, Azure Firewall, Private Endpoints
- Microsoft Purview data classification and sensitivity labels
- HLD/LLD architecture documentation
Typical Deliverables
Threat Detection & SIEM
Deploy and mature Microsoft Sentinel across your environment. KQL-driven analytic rules, detection engineering, automated playbooks, and Defender XDR integration provide a fully operational SOC capability — without standing up a new team.
- Microsoft Sentinel workspace design and deployment
- Data connector configuration — M365 Defender, Entra ID, Azure, Syslog
- Custom KQL analytic rules and scheduled queries
- Threat hunting workbooks and investigation playbooks
- Defender XDR integration — Endpoint, Identity, Cloud Apps, Office 365
- Defender for Cloud CSPM and workload protection
- SOAR automation — Logic Apps / Sentinel playbooks
- Incident triage procedures and escalation runbooks
- MITRE ATT&CK coverage mapping and gap analysis
Typical Deliverables
Threat Modelling
Structured threat modelling for Azure workloads, integration pipelines, and API-driven architectures. Using STRIDE methodology and DFD notation, identify trust boundaries, attack vectors, and control gaps before deployment — not after an incident.
- STRIDE-based threat modelling workshops
- Level 0 and Level 2 Data Flow Diagram (DFD) construction
- Trust boundary identification and attack surface mapping
- Threat catalogue and MITRE ATT&CK technique mapping
- Prioritised mitigations linked to CIS / NIST controls
- API and integration architecture threat analysis
- AI / Copilot data exposure risk modelling
- Threat model documentation for audit and compliance
Typical Deliverables
Compliance & Roadmaps
Translate framework requirements into actionable engineering work. Gap analysis across NIST CSF, ISO 27001, and CIS benchmarks produces a structured roadmap with clear ownership, timelines, and board-ready reporting to drive your security programme forward.
- NIST CSF current-state and target-state assessment
- ISO 27001 gap analysis and readiness review
- CIS benchmark scoring for Azure and M365
- NCSC CAF outcome mapping for commercial organisations
- Structured remediation roadmap with prioritisation
- Board and executive reporting packs
- Policy and procedure documentation
- Control evidence collection for audit readiness
Typical Deliverables
Azure Platform Engineering
Secure, production-ready Azure platform implementations. Function Apps, Logic Apps, API Management, AKS, and event-driven integration architectures — built with Managed Identity patterns, Key Vault integration, and fully codified via Terraform or ARM templates.
- Azure Function App and Logic App design and implementation
- API Management (APIM) — policies, subscriptions, developer portal
- AKS cluster deployment with network policies and RBAC
- Terraform and ARM Infrastructure as Code
- Azure DevOps CI/CD pipeline architecture
- Managed Identity and Key Vault integration patterns
- Event Grid, Service Bus, and messaging architectures
- Application Insights monitoring and alerting
- PowerShell, Python, and KQL automation scripting
Typical Deliverables
Copilot Guardrails, AI Adoption & Purview Data Governance
Microsoft 365 Copilot and Azure OpenAI unlock significant productivity — but without the right controls, they expose sensitive data, create compliance risk, and introduce AI-specific attack vectors. This service covers the full governance stack: from NIST AI RMF risk assessment and CIA Triad alignment through to Purview sensitivity labels, DSPM for AI, and real-time DLP enforcement.
- NIST AI RMF — Map, measure, manage, and govern AI risk across your Microsoft AI estate
- NIST CSF 2.0 Govern function — AI-specific organisational risk policies and accountability structures
- CIA Triad assessment — Evaluate Confidentiality, Integrity, and Availability impact of Copilot and AI workloads
- NCSC CAF alignment — Map AI adoption risk against CAF outcomes A–D for commercial organisations
- Copilot oversharing prevention — Restrict Copilot access to only appropriately labelled and governed data
- Prompt injection hardening — Evaluate and mitigate LLM-specific attack surfaces in Copilot Studio and Azure OpenAI
- Microsoft Purview Information Protection — Sensitivity labels, auto-classification, and unified label policies across M365 and Azure
- DLP policy design and deployment — Endpoint, Exchange, SharePoint, Teams, and OneDrive coverage
- DSPM for AI — Surface data exposed to Copilot via Purview Data Security Posture Management
- Purview Audit & Compliance — eDiscovery, content search, retention policies, and regulatory compliance reporting
- AI adoption roadmap — Phased deployment plan with governance checkpoints and user readiness aligned to NIST CSF 2.0
Typical Deliverables
CIA Triad
Every AI control recommendation is evaluated against Confidentiality (data exposure risk), Integrity (model poisoning and prompt manipulation), and Availability (service reliability and access continuity) to ensure balanced, proportionate governance.
NIST CSF 2.0
The updated framework introduces the Govern function, placing organisational accountability and AI policy at the foundation of the security programme. Implementations are mapped to all six CSF 2.0 functions: Govern, Identify, Protect, Detect, Respond, and Recover.
NCSC CAF
For commercial organisations adopting Copilot or Azure OpenAI, CAF outcomes across all four objectives (A–D: Managing Risk, Protecting, Detecting, and Minimising Impact) are assessed to identify where AI workloads introduce new or elevated risk.
NIST AI RMF
The AI Risk Management Framework's four core functions — Govern, Map, Measure, Manage — structure how we assess and operationalise AI risk, from initial scoping through to ongoing monitoring of your Copilot and Azure AI deployments.
Not sure which service fits?
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