Microsoft security platform engineering

Microsoft security engineering that holds up to review.

THESEFAWAY designs and builds Microsoft Sentinel platforms, detection release pipelines and incident automation. Every change is versioned, tested in a lab before it reaches production, and documented so your team can run it without me.

Platforms and tools I work with

  • Microsoft
  • Microsoft Sentinel
  • Azure
  • Azure Arc
  • Azure Monitor
  • Azure Lighthouse
  • Microsoft Entra ID
  • Logic Apps
  • KQL
  • GitHub
  • GitHub Actions
  • ServiceNow
  • Windows
  • Linux
  • Model Context Protocol

Release model

Nothing reaches a tenant without passing the gate before it.

How a detection moves through the release model I build.

Detection · lifecycle5 stages · 4 gates

  1. dev/

    Author

    Rule written as code, with a stable identity derived from its rule ID.

  2. Peer review
  3. lab

    Validate

    Run against simulated attack telemetry. Results recorded, not remembered.

  4. Evidence
  5. v1.0.0

    Release

    An immutable, versioned copy joins the catalogue. No tenant changes yet.

  6. Code owner
  7. manifest

    Distribute

    A per-destination manifest pins which version lands where.

  8. Approval
  9. GET only

    Verify

    A read-only drift report compares what is deployed with what was released.

Services

Services.

Focused on the Microsoft security stack, where I do my deepest work. Engagements are scoped around a concrete outcome and end with something your team owns.

01

Sentinel platform engineering

Workspace architecture, environment separation and the telemetry that feeds it. I build collection with Azure Arc, the Azure Monitor Agent and data collection rules, covering Windows security events, DNS and Syslog/CEF sources, filtered so you pay for signal rather than noise.

  • Dev, lab and production workspaces with a clear promotion path
  • Data collection rules and cutovers planned to avoid collection gaps
  • Delegated access across tenants with Azure Lighthouse and GDAP, scoped to least privilege
  • Naming standards and onboarding checklists that make the next tenant faster

02

Detection content delivery

Analytics rules treated as a product with releases. I set up the repository, pipeline and review gates that move detection content from authoring to validated, versioned deployment, including across multiple tenants.

  • CI/CD with federated identity, so the pipeline stores no secrets
  • Separate lifecycle and distribution, so each destination gets a pinned version
  • Deterministic rule identities and read-only drift reporting
  • A detection validation lab and a written validation record standard

03

Response automation and integration

Incident workflow that holds together across tools. I connect Sentinel to ServiceNow and build automation rules and Logic Apps with explicit approval steps wherever an action changes something.

  • Incident sync with severity mapping and owner assignment
  • Approval-gated containment workflows
  • Runbooks and an incident taxonomy your analysts will actually use

Selected work

Selected work.

Engineering I have designed and built hands-on. Details are abstracted to protect the environments involved. Each item states honestly where it stands.

  • Validated in test

    Cross-tenant deployment with no stored secretsA GitHub Actions pipeline exchanges a short-lived OIDC token for a federated Entra ID identity, which uses Azure Lighthouse delegated access to deploy analytics rules into a Sentinel workspace in a separate tenant.OIDC tokendeploy-onlyrulespipelineGitHub Actionsfederated identityEntra IDdelegated accessLighthouseseparate tenantSentinelno stored secrets · no guest accounts · no tenant switchingthe pipeline role can deploy content but cannot change access

    Cross-tenant detection deployment with no stored secrets

    A pipeline identity that authenticates through federated credentials, then deploys analytics rules into a separate tenant's Sentinel workspace through delegated resource access. No guest accounts, no tenant switching, and a role that can deploy content but cannot change access.

    Where it stands: deployments into separate test tenants have succeeded end to end.

  • In validation

    Lifecycle and distribution kept separateRules move through dev, lab and a released catalogue, gated by code-owner review. Separate manifests then pin which released version each destination receives.lifecycledev/validatelab/code ownerreleased, versionedcataloguemanifestdest. A · v1.0manifestdest. B · v1.1manifestdest. C · v1.1folders carry lifecyclemanifests carry distribution

    A release and distribution model for detection content

    Folders carry lifecycle and manifests carry distribution, so one catalogue can serve several destinations at different pinned versions. Four content classes, from vendor templates to client-specific rules, each get their own validation route, with code-owner review before anything is released.

    Where it stands: repository, workflows and review gate are built; the first full run from authoring to production is in progress.

  • In validation

    Deterministic identity and a read-only drift reportEach rule's identity is derived from its rule ID, so the same detection has the same identity in every workspace. A read-only report compares what is deployed with the released version.derivesourcerule IDdeterministicderived identityworkspace 1workspace 2workspace 3GET onlydriftsame detection, same identity, in every workspace

    Deterministic rule identity and drift reporting

    Rule identities derived from the rule ID rather than assigned by the portal, so the same detection is recognisable in every workspace. A read-only report then shows where a deployed rule differs from its released version.

    Where it stands: implemented and in review.

  • Running

    Additive cutover with a second data collection ruleAn Arc-enabled host running the Azure Monitor Agent keeps its existing data collection rule to the development workspace, and a second rule association sends the same events to production, without re-onboarding.security + DNSsame eventsArc + AMAhostexistingDCR 1addedDCR 2authoringdev workspaceproductionprod workspacesecond association added: no re-onboarding, and dev keeps its live feed

    Additive telemetry cutover to a new production workspace

    Windows security events and DNS telemetry routed to a new production workspace by adding a second data collection rule association, rather than re-onboarding the host. Development kept its live feed for detection authoring while production began receiving the same events.

    Where it stands: both workspaces are receiving data.

  • Validated in test

    Severity-based incident sync to ServiceNowAutomation rules select Sentinel incidents by severity when they are created and when they escalate, a Logic App creates or updates the ServiceNow incident, and owner assignment syncs in both directions.severitysyncowner assignment, both waysSentinelincidenton create / escalateautomationintegrationLogic AppServiceNowincidentan incident that starts informational and escalates still reaches the service desk

    Incident sync between Sentinel and ServiceNow

    Automation rules that select incidents for sync by severity on creation and on escalation, so an incident that starts informational and later becomes serious still reaches the service desk. Owner assignment carries across in both directions.

    Where it stands: all three sync scenarios passed in the development environment.

  • In validation

    Three access planes, decided separatelyBilling, Azure resource control and directory identity are treated as three separate decisions. Azure Lighthouse handles resource access, GDAP handles identity, and each service tier receives only the roles it needs.plane 1billingplane 2Azure resourcesplane 3identityits own decisionAzure LighthouseGDAPleast privilegeroles per tierread-only: provenelevated: in validation

    A delegated access model built on separate planes

    Billing, Azure resource control and directory identity treated as three separate decisions instead of one. Azure Lighthouse handles resource access, GDAP handles the identity plane, and each tier of service gets only the roles it needs.

    Where it stands: read-only delegated access is proven on a test tenant; elevated response actions are still being validated.

  • Proof of concept

    An MCP gateway with read-only tools and approval-only containmentAn AI assistant reaches Sentinel only through an MCP gateway. Incident queries are read-only. Containment can only produce an approval request for a person; there is no code path that executes it.approvalclientAI assistantcontrolled toolsMCP gatewayread-onlyquery incidentsrequest onlycontainmentSentinelapprovesanalystno execution path

    Governed AI access to security tooling

    A gateway that exposes Sentinel data to an AI assistant through a small set of controlled tools. Incident queries are read-only. Containment can be requested but never executed: the tool produces an approval request, and no code path exists that could act on its own.

    Where it stands: a four-stage local proof of concept, from mock server to a real read-only query, built and verified.

Approach

Approach.

A typical engagement follows the same order, because each step makes the next one safer.

  1. Map what exists

    Inventory workspaces, data sources, rules, identities and dependencies before proposing change. Nothing gets decommissioned on assumption.

  2. Decide in writing

    Short decision records for anything structural: what was chosen, what was rejected and why. You keep them after I leave.

  3. Build in a lab first

    Detections and response workflows prove themselves against simulated activity before they touch a production tenant.

  4. Promote through gates

    Review, evidence and approval at each step, enforced by the pipeline rather than by good intentions.

  5. Hand over

    Runbooks, onboarding checklists and a clear record of what is proven and what is still being tested.

About

About.

THESEFAWAY is a founder-led practice. When you work with it, you work directly with the engineer who designs and builds the system.

I’m Sefa, the founder. My work sits where security operations meets platform engineering: Microsoft Sentinel and Azure, the telemetry pipelines underneath them, the delivery systems that keep detection content consistent across environments, and the automation that connects incidents to the people handling them.

Alongside client work, I build our own software with my partners, Zeph (engineering), Jimmy (front end) and Prince (project management), including the Trojan vulnerability scanner. I work iteratively and test in real environments. I write documentation that is plain, precise and scoped, and I keep the line between what is proven and what is still being tested visible to everyone involved.

Where I’ve delivered services

  1. 2026 – nowVectorUSACyber Security Engineer, contract. Platform design and documentation for a new co-managed SOC service.
  2. 2023 – 2026IndiviorIT Security Engineer, contract, after two years as IT Security Analyst. Security operations, automation and the software side of IT security.
  3. 2020 – 2023AIENAIWebsite Vulnerability Analyst and Interaction Designer; before that, Senior Interaction and Motion Designer.
  4. 2021Zebu DigitalDigital Designer, contract.

I started in interaction and motion design, which is why the things I build are meant to be easy to use as well as hard to break.

Microsoft, Microsoft Sentinel, Azure and Azure Lighthouse are trademarks of the Microsoft group of companies. THESEFAWAY is independent and not affiliated with Microsoft. ServiceNow is a trademark of ServiceNow, Inc.

Get in touch.

Tell me what you run today and what you want to be true in three months. I will reply with whether I can help, and if not, who might.

Email
admin@thesefaway.com

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