This rule identifies a potential port scan. A port scan is a method utilized by attackers to systematically scan a target system or network for open ports, allowing them to identify available services and potential vulnerabilities. By mapping out the open ports, attackers can gather critical information to plan and execute targeted attacks, gaining unauthorized access, compromising security, and potentially leading to data breaches, unauthorized control, or further exploitation of the targeted system or network. This rule defines a threshold-based approach to detect connection attempts from a single source to a wide range of destination ports.

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This rule identifies a potential network sweep. A network sweep is a method used by attackers to scan a target network, identifying active hosts, open ports, and available services to gather information on vulnerabilities and weaknesses. This reconnaissance helps them plan subsequent attacks and exploit potential entry points for unauthorized access, data theft, or other malicious activities. This rule defines a threshold-based approach to detect multiple connection attempts from a single host to numerous destination hosts over commonly used network services.

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This rule identifies a potential SYN-Based port scan. A SYN port scan is a technique employed by attackers to scan a target network for open ports by sending SYN packets to multiple ports and observing the response. Attackers use this method to identify potential entry points or services that may be vulnerable to exploitation, allowing them to launch targeted attacks or gain unauthorized access to the system or network, compromising its security and potentially leading to data breaches or further malicious activities. This rule defines a threshold-based approach to detect connection attempts from a single source to a large number of unique destination ports, while limiting the number of packets per port.

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A supervised machine learning model has identified a DNS question name that is predicted to be the result of a Domain Generation Algorithm (DGA), which could indicate command and control network activity.

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A supervised machine learning model has identified a DNS question name with a high probability of sourcing from a Domain Generation Algorithm (DGA), which could indicate command and control network activity.

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A supervised machine learning model has identified a DNS question name that used by the SUNBURST malware and is predicted to be the result of a Domain Generation Algorithm.

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A statistical model has identified command-and-control (C2) beaconing activity. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network.

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A statistical model has identified command-and-control (C2) beaconing activity with high confidence. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network.

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