List Cloud Persistence Activities By User At Risk
Description This guide explains how to detect cloud persistence activities performed by users identified as at risk using KQL queries.
Read MoreWhere Every Failure Becomes A Manual
Description This guide explains how to detect cloud persistence activities performed by users identified as at risk using KQL queries.
Read MoreThis KQL query identifies discovery events performed by users marked as at risk within an Azure environment. It targets actions
Read MoreAMSI script detection KQL query is a crucial tool for monitoring Windows environments where the Antimalware Scan Interface detects potentially
Read MoreDetect anomalous group policy discovery by leveraging KQL queries to identify devices performing group policy scans they have not executed
Read MoreAdversaries can use LDAP to collect environment information. The query below can be used to detect anomalous amounts of LDAP
Read MoreThis guide uses KQL to detect executed LDAP queries originating from compromised devices. Monitoring LDAP traffic is critical for identifying
Read MoreDetecting Azure Monitor Agent (AMA) connector failures using a Kusto Query Language (KQL) script focused on Syslog data enables rapid
Read MoreDetecting Azure Monitor Agent connector failures with KQL is essential for maintaining consistent log ingestion and security alerting. This query
Read MoreAdversaries gaining access through brute force may immediately change a compromised account’s password to maintain persistence without raising alarms. This
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