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Security Operations & Automation

Overview

Buying security tools is easy. Making them detect real attacks, run reliably, and take the manual work off your team is where most companies stall.
We build, tune, and automate your defenses, detection that catches what matters, and automation for the repetitive work your team shouldn't be doing by hand, and we deliver it as code you own.

SIEM & Detection Engineering

We design, deploy, and tune Microsoft Sentinel so it actually detects the attacks that matter, and we deliver the detections as code, KQL analytics and hunting rules, deployed as Terraform, that your team owns. your team owns. Not a dashboard we watch for you, a detection capability you run.

The Process

  1. Define what you need to detect

    We start from the threats and attack paths relevant to your environment, the same ones our red team would use, and define the detection use cases that matter. Not a generic rule pack.

  2. Design the data and architecture

    We decide which log sources you actually need, size ingestion for cost, and design the Sentinel workspace and connectors. Cost is controlled before it runs away, not after.

  3. Build detections as code

    We write and version the analytics rules and hunting queries in KQL, deployed as Terraform, with response playbooks as Logic Apps, all version-controlled in a repository, mapped to MITRE ATT&CK.

  4. Tune out the noise

    We reduce false positives, tune thresholds, and validate detections against real attack techniques, so your team sees signal instead of alert fatigue.

  5. Hand over and iterate

    Your team owns the detection content and can maintain it without us. As new threats and log sources appear, we extend the coverage.

The Outcomes

  • A Sentinel deployment tuned to detect the attacks that actually matter to you

  • Detection content as code your team owns and can maintain

  • Ingestion sized and governed for cost, not runaway bills

  • Fewer false positives, and coverage you can map to MITRE ATT&CK

AI-Driven Security Automation

We engineer AI-driven automation across your security operations: offensive, defensive, and cloud. Automated adversary emulation and attack simulation, agentic detection and response, cloud monitoring and remediation: the complex, repetitive work your team runs by hand, turned into automated workflows and agents you own. Built with agentic AI, delivered as code, human-governed on the actions that matter.

The Process

  1. Map the work across your operations

    We look across your offensive, defensive, and cloud security work for what's repetitive, slow, or manual: adversary emulation and attack-path simulation, asset and vulnerability discovery, detection and incident response, cloud monitoring and host remediation. We target where automation and AI give back the most.

  2. Design agentic workflows with guardrails

    We design the automations and agents around how your team operates, using LLMs and agentic AI where they earn their place. We decide upfront what runs autonomously and where a human approves, so you keep control of every consequential action.

  3. Build it as code

    We build the automation in Python and infrastructure as code (Terraform), integrated with the tools you already run, red and blue team tooling, Sentinel, your cloud. Version-controlled, documented, custom to your environment, and yours.

  4. Prove it, then widen

    We run each workflow against real cases, a real attack path, a real incident, a real cloud event, tune it until you trust it, then expand what it handles. The AI proposes, your team disposes.

  5. Hand over and extend

    You own the code and can run and change it without us. As new work across your operations proves worth automating, we automate that too.

The Outcomes

  • Offensive, defensive, and cloud security work automated, from adversary emulation to incident response

  • Custom agents and workflows built around how your team operates

  • Delivered as code (Python + Terraform) your team owns and can change

  • AI and agents where they add leverage, with a human in the loop on every action that matters

JML / Identity Lifecycle Automation

We automate the joiner, mover, and leaver process across Entra ID, Google, or Okta, and the SaaS applications connected to it, so access is granted, changed, and revoked automatically, and every change is logged as audit-ready evidence. We deliver the automation as code, Terraform for your identity-provider and application configuration, Python for the lifecycle logic and connectors, so it runs on your stack and your team owns it."
No more orphaned accounts, no more manual offboarding, no more quarterly access-review scramble.

The Process

  1. Map your identity lifecycle

    We document how joiners, movers, and leavers flow today across your HR system, your identity provider, and connected applications, and where access sprawl and orphaned accounts come from.

  2. Define the access model

    We agree the roles, entitlements, and rules that decide who gets what, so provisioning becomes deterministic instead of ad hoc.

  3. Build the automation

    We connect your HR trigger to your identity provider and your applications, and automate provisioning on join, access changes on role change, and full deprovisioning, accounts, sessions, and tokens, on exit. We work with whatever provider and SaaS stack you run, not a single vendor.

  4. Automate access recertification

    We schedule periodic access reviews that route to the right approver and revoke anything not re-approved, producing the evidence auditors ask for automatically.

  5. Hand over and maintain

    The automation runs on your stack and is documented for your team. We keep it aligned as your applications and roles change.

The Outcomes

  • No orphaned accounts and no lingering access

  • Access reviews that run themselves and produce audit-ready evidence

  • Proof of least-privilege access for ISO 27001, NIS2, and SOC 2 auditors

  • Identity automation delivered as code (Terraform + Python) your team owns