Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects anomalous outbound SMTP (port 25) traffic originating from a NetScaler ADC or Gateway appliance. Since these appliances have no legitimate business requirement to initiate outbound SMTP communication, such traffic is a strong indicator of post-compromise activity, potentially used for command and control or data exfiltration.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
This rule detects potential Browser-in-the-Browser (BitB) phishing attacks by identifying suspicious browser pop-up behavior (using window.open flags, hidden address/toolbars) on non-identity-provider domains, followed shortly by credential submission patterns on the same device. This pattern mimics legitimate OAuth or SSO windows to harvest user credentials.
Detects a multi-stage compromise sequence involving anomalous authentication followed by VPN session establishment and a burst of outbound connections from Citrix ADC/Gateway appliances. Tightened to reduce false positives from legitimate admin access, routine VPN sessions, and authorized appliance telemetry/updates.
Detects TLS connections to a specific, potentially adversary-controlled ScreenConnect relay infrastructure endpoint. Adversaries frequently abuse legitimate remote access tools like ScreenConnect for command and control purposes.
Detects potential Cobalt Strike or Sliver command and control (C2) beaconing behavior by analyzing network proxy, firewall, and flow logs for common C2 URI patterns, known malicious JA3/JA3S TLS fingerprints, and consistent periodic communication intervals (low jitter) characteristic of automated beacons.
Detects indicators associated with the ChatGPT Custom GPT ClickFix campaign across process, network connection, DNS, and HTTP telemetry: known malicious file hashes, C2 IP addresses, the chattypetty.com domain, and known payload-hosting URLs.
This rule monitors network traffic from CommonSecurityLog data to detect bidirectional communication between NetScaler appliances and known malicious infrastructure associated with the CVE-2026-88772 campaign, which is indicative of command-and-control activity.
Detects browser processes performing JSON-RPC network connections to known public blockchain node providers, a network behavior characteristic of the EtherHiding technique used by the ErrTraffic MaaS platform to resolve C2 infrastructure via smart contracts. This rule identifies the network-side beaconing and should be correlated with suspicious process execution chains (e.g., browser-spawned PowerShell/cmd).
Detects a multi-stage compromise sequence involving anomalous authentication followed by VPN session establishment and a burst of outbound connections from Citrix ADC/Gateway appliances. Tightened to reduce false positives from legitimate admin access, routine VPN sessions, and authorized appliance telemetry/updates.
Detects DNS queries and TLS SNI traffic associated with known lookalike domains used by the threat actor TA419 for organization impersonation, which are commonly utilized in spearphishing campaigns.
Detects DNS queries and TLS SNI traffic associated with known lookalike domains used by the threat actor TA419 for organization impersonation, which are commonly utilized in spearphishing campaigns.
This rule detects outbound network connections directed at a known IP address associated with Akira ransomware infrastructure. The rule specifically monitors for communication with 64.227.4.134, which has been identified as a C2 node utilizing GOST tunnels. This behavior is indicative of established C2 connectivity by Akira ransomware actors.
Detects process/file hashes associated with the ChatGPT Custom GPT ClickFix
campaign via Windows process_creation telemetry. Split from the combined IOC
hunt: Sigma supports only one logsource per rule, so IP/domain/URL matching live
in separate network_connection and dns_query rules.
campaign via Windows process_creation telemetry. Split from the combined IOC
hunt: Sigma supports only one logsource per rule, so IP/domain/URL matching live
in separate network_connection and dns_query rules.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
Detects a multi-stage compromise sequence involving anomalous authentication followed by VPN session establishment and a burst of outbound connections from Citrix ADC/Gateway appliances. Tightened to reduce false positives from legitimate admin access, routine VPN sessions, and authorized appliance telemetry/updates.
Detects TLS connections to a specific, potentially adversary-controlled ScreenConnect relay infrastructure endpoint. Adversaries frequently abuse legitimate remote access tools like ScreenConnect for command and control purposes.
Detects ScreenConnect client processes initiating outbound network connections to external cloud relay addresses (typically *-relay.screenconnect.com) from locations outside of standard Program Files directories. This behavior is indicative of unauthorized, standalone, or adversary-deployed ScreenConnect instances attempting to establish a Command and Control (C2) channel, bypassing standard IT-managed deployment pathways.
The following analytic detects DNS queries initiated by the Windows AI Platform to domains associated with Hugging Face, OpenAI, and other popular providers of machine learning models and services. Monitoring these DNS requests is important because it can reveal when systems are accessing external AI platforms, which may indicate the use of third-party AI resources or the transfer of sensitive data outside the organization’s environment. Detecting such activity enables organizations to enforce data governance policies, prevent unapproved use of external AI services, and maintain visibility into potential data exfiltration risks. Proactive monitoring provides better control over AI model usage and helps safeguard organizational data flows.
This rule performs indicator-based detection for the SectopRAT malware. It monitors network activity for connections to known command-and-control (C2) IP addresses and backup domains, as well as file and process creation events matching known malicious SHA256 hashes associated with the malware.
Detects outbound network connections from Citrix NetScaler appliances that exhibit high periodic regularity (beaconing behavior) towards rare external destinations. This pattern is indicative of potential command and control (C2) communication, possibly following the exploitation of vulnerabilities like CVE-2026-88771/88772.
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