Kusto Query Language (KQL) is a powerful tool for cybersecurity professionals, enabling efficient log querying, threat hunting, and data analysis in Microsoft Sentinel and Azure Data Explorer. If you’ve ever wondered how experts like Steven Lim generate a steady stream of insightful KQL queries, the answer lies in continuous practice, creativity, and real-world application.
You Should Know: Essential KQL Commands & Techniques
1. Basic KQL Query Structure
SecurityEvent | where EventID == 4625 // Failed logon attempts | summarize FailedAttempts = count() by Account | sort by FailedAttempts desc
This query identifies brute-force attacks by counting failed logon attempts per account.
2. Hunting for Suspicious Processes
DeviceProcessEvents
| where FileName in~ ("powershell.exe", "cmd.exe", "wmic.exe")
| where InitiatingProcessFileName != "explorer.exe"
| project Timestamp, DeviceName, AccountName, FileName, CommandLine
Detects unusual process executions outside normal user activity.
3. Detecting Ransomware Patterns
DeviceFileEvents | where ActionType == "FileCreated" | where FileName endswith ".encrypted" or FileName endswith ".locked" | summarize FileCount = count() by DeviceName | where FileCount > 5
Identifies potential ransomware activity by tracking suspicious file extensions.
4. Analyzing Network Anomalies
DeviceNetworkEvents | where RemoteIPType == "Public" | summarize ConnectionCount = count() by RemoteIP | where ConnectionCount > 100 | join kind=inner (IPGeoData) on RemoteIP | project RemoteIP, Country, ConnectionCount
Highlights potential C2 servers by detecting excessive outbound connections.
5. Advanced Threat Hunting with Joins
let MaliciousIPs = datatable(IP:string) [ "1.1.1.1", "2.2.2.2", "3.3.3.3" ]; DeviceNetworkEvents | where RemoteIP in (MaliciousIPs) | extend GeoData = geo_info_from_ip_address(RemoteIP) | project Timestamp, DeviceName, RemoteIP, GeoData.country
Cross-references traffic with known malicious IPs.
What Undercode Say
Mastering KQL requires hands-on practice and real-world threat analysis. By integrating these queries into your cybersecurity workflow, you can enhance threat detection, automate investigations, and respond faster to incidents.
Expected Output:
- Failed login attempts report
- Suspicious process execution alerts
- Ransomware file creation detection
- High-frequency external connections
- Geo-mapped malicious IP traffic
Keep refining your KQL skills—every query you write strengthens your cybersecurity expertise.
Prediction
As cyber threats evolve, KQL will become even more critical in threat detection, with AI-enhanced query recommendations and automated response integrations. Stay ahead by continuously improving your KQL knowledge.
References:
Reported By: 0x534c Ever – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
