Recently, I documented a real-world cloud security investigation where I used Microsoft Sentinel to detect and contain a potential ransomware attack before full system compromise.
In this case study, I walk through the end-to-end incident response process, including:
🔎 Detecting brute-force authentication attempts
📊 Investigating suspicious identity activity using KQL queries
🧠Mapping attacker behaviour to the MITRE ATT&CK framework
âš¡ Rapid containment of compromised accounts
📉 Reducing Mean Time To Detect (MTTD) to ~30 minutes and containing the threat within ~2.5 hours
The goal of this write-up was to demonstrate how modern cloud SIEM platforms like Microsoft Sentinel can enable proactive threat detection and rapid response in Azure environments.
Cyber threats targeting cloud identities are increasing rapidly, and having strong monitoring, alerting, and threat-hunting capabilities is essential for security teams.
I hope this breakdown helps other SOC analysts, cloud engineers, and security professionals improve their investigation workflows.
Canonical URL:
https://medium.com/@davidud2016/how-i-handled-a-cloud-security-incident-end-to-end-using-microsoft-sentinel-5ed4a301e3ea
Happy to discuss investigation techniques, KQL queries, or Sentinel workflows with anyone working in **cloud security and incident response.
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