Subash Ghimire
@iamsubashgTrusted contributorCompletionist
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92 detections
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The rule detects potential execution or presence of EDRKiller or similar tools by matching known malicious hashes from an external source against telemetry from Defender for Endpoint to help security analysts identify compromised endpoints, investigate delivery methods, and take remediation actions.
This KQL query detects potential threats by analyzing recent network traffic logs for activity involving suspicious ports, using an external CSV list of historically exploited ports.
This query detects the installation of a potentially unwanted or suspicious application, correlates it with network activity to public IPs, indicating possible telemetry, data exfiltration, or command and control behavior. The rule appears to be valid.
This KQL query detects network traffic to or from suspicious ports by joining firewall logs (CommonSecurityLog) with an external, regularly updated list of known suspicious ports. It specifically looks for accepted or passed connections to these ports, indicating potential exploitation attempts or unauthorized communication channels used by threat actors.
This rule detects suspicious activities related to Remote Monitoring and Management (RMM) tools by querying various data sources. It identifies processes, file signatures, network connections, and firewall logs associated with known RMM tools and domains, helping to uncover potential security threats. The rule leverages an external IOC list for RMM tool names, file signatures, and associated domains.
This rule detects suspicious file write and network activity that may indicate data exfiltration from a Windows Server using common tools like curl, ftp, or powershell. It correlates file creation/modification events with outbound network connections made by known exfiltration tools within a 5-minute window. This is useful for identifying insider threats, compromised servers, and automated exfiltration scripts.
This rule detects the creation or modification of registry keys and values under "HKEY_CURRENT_USER\SOFTWARE\Microsoft\OneDrive\Personal". This activity can indicate unauthorized personal OneDrive usage within an organization, which could be leveraged for data exfiltration, establishing persistence through cloud sync, or user profile manipulation. It is particularly useful for identifying insider threats, compromised servers, or automated exfiltration scripts.
This KQL query searches the ExposureGraphNodes table in Microsoft Defender XDR or Sentinel to identify user accounts whose credentials have been leaked. It focuses on nodes categorized as "identity" and labeled as "user", then extracts detailed identity-related properties such as: Display name, UPN, email address, Account status (enabled/disabled), Job title, department, phone, address, Source provider (e.g., Azure AD, on-prem AD), Account creation time, and whether the account's credentials have been leaked. The query filters and enriches this data, and presents it in a clean, readable format for hunting or triage.
This rule detects an unusually high volume of DNS queries originating from a single device within a one-hour window. This behavior can be indicative of various malicious activities such as DNS tunneling for command and control, data exfiltration, or extensive reconnaissance.
This rule detects successful Remote Desktop Protocol (RDP) connections by monitoring network events where the remote port is 3389 and the connection action type is 'ConnectionSuccess'. It aims to identify potential unauthorized access, lateral movement, or audit remote administration practices.
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