Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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KQL Query
The following analytic detects instances of DLLHost.exe running without command line arguments while establishing a network connection. This behavior is identified using Endpoint Detection and Response (EDR) telemetry, focusing on process execution and network activity data. It is significant because DLLHost.exe typically runs with specific arguments, and its absence can indicate malicious activity, such as Cobalt Strike usage. If confirmed malicious, this activity could allow attackers to execute code, move laterally, or exfiltrate data, posing a severe threat to the network's security.
KQL Query from file: Hunting CVE-2025-31324
KQL Query
KQL Query from file: DefenderXDR Weekly OSINT Indicators Scan 24022025
KQL Query from file: DefenderXDR Weekly OSINT Indicators Scan 19052025
KQL Query
KQL Query from file: Hunting Aqua Blizzards
KQL Query from file: Muddled Libra
This YARA rule detects the ChaosRAT backdoor by identifying specific byte sequences related to its network communication, system information gathering, and file download capabilities. The rule includes three distinct versions of these functionalities, indicating evolution or different variants of the malware. Detection relies on the presence of these unique byte patterns within executable files, specifically ELF files as indicated by the magic byte check.
Visualises the top 10 users with click attempts on URLs in emails detected as spam, helping analysts identify risky user behaviour and potential targets.
Based on Defender for Office 365 workbook: https://techcommunity.microsoft.com/blog/microsoftdefenderforoffice365blog/part-2-build-custom-email-security-reports-and-dashboards-with-workbooks-in-micr/4411303
Based on Defender for Office 365 workbook: https://techcommunity.microsoft.com/blog/microsoftdefenderforoffice365blog/part-2-build-custom-email-security-reports-and-dashboards-with-workbooks-in-micr/4411303
Summarizes URL click events by action type to help analysts understand user click behavior and policy effectiveness.
Based on Defender for Office 365 workbook: https://techcommunity.microsoft.com/blog/microsoftdefenderforoffice365blog/part-2-build-custom-email-security-reports-and-dashboards-with-workbooks-in-micr/4411303
Based on Defender for Office 365 workbook: https://techcommunity.microsoft.com/blog/microsoftdefenderforoffice365blog/part-2-build-custom-email-security-reports-and-dashboards-with-workbooks-in-micr/4411303
Visualises the top 10 users with click attempts on URLs in emails detected as phishing, helping analysts identify risky user behaviour and potential targets.
Based on Defender for Office 365 workbook: https://techcommunity.microsoft.com/blog/microsoftdefenderforoffice365blog/part-2-build-custom-email-security-reports-and-dashboards-with-workbooks-in-micr/4411303
Based on Defender for Office 365 workbook: https://techcommunity.microsoft.com/blog/microsoftdefenderforoffice365blog/part-2-build-custom-email-security-reports-and-dashboards-with-workbooks-in-micr/4411303
Detects network communication to known Prometei botnet distribution and command-and-control (C2) infrastructure.
Detects an executable initiating a network connection to "ngrok" tunneling domains.
Attackers were seen using this "ngrok" in order to store their second stage payloads and malware.
While communication with such domains can be legitimate, often times is a sign of either data exfiltration by malicious actors or additional download.
Attackers were seen using this "ngrok" in order to store their second stage payloads and malware.
While communication with such domains can be legitimate, often times is a sign of either data exfiltration by malicious actors or additional download.
This analytic detects new UDP communication between a source and destination workload pair within a Kubernetes cluster. It uses Network Performance Monitoring (NPM) metrics from an OTEL collector via Splunk Observability Cloud. The detection compares network activity over the last hour with the past 30 days to identify new inter-workload communication. Such changes in network behavior can indicate potential security threats or anomalies, including unauthorized connections that may lead to data breaches, privilege escalation, lateral movement, or disruption of critical services.
This analytic identifies newly observed TCP communication between source and destination workloads within a Kubernetes cluster. It leverages Network Performance Monitoring metrics to compare recent network activity with historical data (past 30 days) to detect new inter-workload communications. Such new connections can indicate changes in application behavior or potential security threats, including unauthorized access, lateral movement, privilege escalation, data exfiltration, or disruption of critical services.
This analytic detects the execution of the `Get-NetTcpconnection` PowerShell cmdlet using PowerShell Script Block Logging (EventCode=4104). This cmdlet lists network connections on a system, which adversaries may use for situational awareness and network discovery. Monitoring this activity is crucial as it can indicate reconnaissance efforts by an attacker. If confirmed malicious, this behavior could allow an attacker to map the network, identify critical systems, and plan further attacks, potentially leading to data exfiltration or lateral movement within the network.
Detects potential Active Directory enumeration via LDAP
Detects connections with Azure Front Door (known legitimate service that can be leveraged for C2)
that fall outside of known benign behavioral baseline (not using common apps or common azurefd.net endpoints)
that fall outside of known benign behavioral baseline (not using common apps or common azurefd.net endpoints)
Detects initiated network connections to crypto mining pools
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