The Challenge

As Lead Security Engineer engaged by a major financial services enterprise, I was brought in to address a severe alert fatigue problem that was undermining the effectiveness of the Security Operations Centre. The volume of low-fidelity alerts generated across the organisation's Microsoft security stack meant that actionable intelligence was buried in noise — critical threats were being identified and remediated too slowly, increasing dwell time and exposing the organisation to growing business risk.

• High alert volume with a poor signal-to-noise ratio — analysts were manually triaging thousands of low-fidelity notifications with no structured prioritisation or suppression in place
• No centralised visibility across the threat landscape — intelligence was fragmented across multiple tools with no single operational picture available to the SOC
• Executive reporting was manual and inconsistent, with no real-time board-level view of the organisation's security posture or trending threat activity

The Approach

I designed and built an interactive Microsoft Sentinel dashboard tailored for dual purpose: real-time SOC monitoring and automated executive-level security reporting.

I authored custom KQL (Kusto Query Language) detection rules to correlate low-fidelity signals into high-confidence incidents, with all detection logic mapped directly to the MITRE ATT&CK framework to support a threat-informed defence posture. I then designed and implemented automated alert suppression rules targeting known false-positive patterns — reducing the volume of noise reaching analyst queues by 65% from baseline. I structured the dashboard into two distinct views: an analyst operational view surfacing prioritised, high-confidence incidents, and an executive summary view delivering automated board-level reporting without manual data collation.

The Results

I delivered a production-ready, MITRE ATT&CK-aligned threat intelligence dashboard that gave the SOC an immediate, unified operational picture and freed analysts from the noise of low-fidelity alerts — shifting the team's posture from reactive triage to proactive, intelligence-led hunting.

Business & Security Impact

• Alert volume reduced by 65% through structured KQL detection tuning and automated false-positive suppression, returning analyst focus to genuine, high-confidence threats
• Mean Time To Respond (MTTR) improved by centralising all critical threat telemetry onto a single Microsoft Sentinel pane of glass, eliminating tool-switching and manual correlation
• Executive security reporting fully automated — board-level dashboards now delivered without manual data collation, improving governance visibility and reporting consistency
• Detection logic aligned to MITRE ATT&CK, enabling threat-informed defence and supporting compliance with threat intelligence and detection engineering requirements
• Scalable, maintainable KQL ruleset established — the detection framework continues to operate and evolve with the threat landscape without ongoing consultancy dependency

My deep, hands-on experience with Microsoft Sentinel's KQL query language and detection engineering — built across multiple financial services deployments — allowed me to identify and suppress the specific false-positive patterns driving the alert fatigue from the first week of the engagement, rather than requiring extended baselining periods. The 65% reduction was achieved before the full dashboard was even deployed.