MicrosoftMicrosoft Sentinel

    Analytics & Detection

    Analytics rules and ML-driven detection that turn data into high-fidelity incidents.

    Microsoft Sentinel Analytics & Detection turns raw security data into high-fidelity incidents — with built-in and custom analytics rules, machine-learning anomaly detection, user and entity behaviour analytics (UEBA), and Fusion correlation that stitches low-fidelity signals into multistage-attack detections. Faltrox builds and tunes the detection logic as part of a managed SOC.

    Talk to an expertHow we deliver it

    Overview

    What Analytics & Detection is

    A SIEM is only as good as its detection logic — raw data without effective analytics is just noise. Microsoft Sentinel’s Analytics & Detection turns that data into high-fidelity incidents through a combination of built-in and custom analytics rules, machine learning, behavioural analytics, and correlation.

    It provides scheduled and near-real-time analytics rules, built-in detections mapped to MITRE ATT&CK, machine-learning anomaly detection, User and Entity Behaviour Analytics (UEBA) to baseline and surface anomalies, and Fusion — Microsoft’s ML correlation that stitches together low-fidelity signals across sources into high-fidelity multistage-attack detections. That is what cuts alert fatigue and surfaces real attacks. Faltrox builds and tunes the detection logic to your environment as part of the managed SOC it runs.

    Coverage

    What it protects

    The platforms, threats, and surfaces this product is built to defend.

    01

    ML Detection

    Machine-learning anomaly detection surfaces threats that rules miss.

    02

    Fusion Correlation

    Stitches low-fidelity signals into high-fidelity multistage-attack detections.

    03

    UEBA

    User and entity behaviour analytics baseline and surface anomalies.

    04

    Analytics Rules

    Built-in and custom scheduled and near-real-time analytics rules.

    05

    MITRE ATT&CK

    Built-in detections mapped to the MITRE ATT&CK framework.

    06

    Reduced Alert Fatigue

    High-fidelity incidents cut the noise analysts face.

    How it works

    The mechanism

    How the product moves from signal to protected state, step by step.

    1. 01

      Rules

      Built-in and custom analytics rules detect known threats and correlate them into incidents.

    2. 02

      Machine Learning

      ML anomaly detection and UEBA surface anomalies and behaviours rules cannot catch.

    3. 03

      Fusion

      Fusion correlation stitches low-fidelity signals across sources into high-fidelity multistage detections.

    4. 04

      Map to ATT&CK

      Detections map to MITRE ATT&CK so tactics and coverage are clear.

    5. 05

      Operate

      Faltrox builds and tunes the detection logic to your environment as part of a managed SOC.

    Capabilities

    Key capabilities

    Analytics Rules

    Built-in and custom scheduled and near-real-time analytics rules.

    ML Anomaly Detection

    Machine-learning anomaly detection surfaces threats rules miss.

    UEBA

    User and entity behaviour analytics baseline behaviour and surface anomalies.

    Fusion Correlation

    ML correlation stitches low-fidelity signals into high-fidelity multistage-attack detections.

    MITRE ATT&CK Mapping

    Built-in detections mapped to MITRE ATT&CK for clear coverage and tactics.

    Custom Detection

    Author custom detections tuned to your environment and threats.

    Reduced False Positives

    High-fidelity detection cuts alert fatigue and false positives.

    Sentinel Integration

    Integrated across the Sentinel platform and unified operations.

    Works with

    Part of the platform

    Microsoft products this pairs with, and the Faltrox services that operate it.

    Delivery

    You buy the outcome, not the console

    Managed by Faltrox

    Faltrox licenses, deploys, and tunes Microsoft Analytics & Detection for your environment, then runs it as part of a managed service, so you get the protection without staffing another security console.

    See the service

    FAQ

    Common questions

    01What is Fusion?

    Fusion is Microsoft’s machine-learning correlation that stitches together low-fidelity signals across many sources into high-fidelity, multistage-attack detections — so an attack that appears as scattered weak signals is surfaced as one high-confidence incident, which is central to cutting alert fatigue.

    02Does it detect beyond rules?

    Yes — alongside built-in and custom analytics rules, it uses machine-learning anomaly detection and User and Entity Behaviour Analytics (UEBA) to surface threats and behaviours that static rules cannot catch, like anomalous access or lateral movement.

    03Are detections mapped to a framework?

    Yes — built-in detections are mapped to the MITRE ATT&CK framework, so you can see which tactics and techniques you have coverage for and where the gaps are, which guides detection engineering.

    04Can we write our own detections?

    Yes — custom analytics rules let you author detections tuned to your environment and threats, alongside the built-in ones. Faltrox builds and tunes that custom detection logic for the SOC we run.

    05How does Faltrox operate it?

    We build and tune the analytics rules, ML detections, and Fusion correlation to your environment, map coverage to MITRE ATT&CK, and continuously refine detection to cut false positives — as part of the managed SOC we deliver.

    Start an engagement

    Secure what’s next.

    Speak with the engineering team to define scope, walk through the methodology, and decide whether Faltrox is the right team to test and run your environment.

    Contact us