Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential Command and Control (C2) beaconing activity by identifying periodic outbound network connections from suspicious or non-browser processes. It analyzes the time deltas between successful network connections; if the standard deviation of these intervals is low (indicating consistent timing) and a sufficient number of connections occur, it flags the behavior as a potential C2 heartbeat.
This rule detects successful or failed logon attempts originating from IP addresses identified by threat intelligence as associated with botnets, command and control (C2) infrastructure, or proxies. The rule specifically looks for 'LogOn' or 'FailedLogOn' activity types where the source IP's threat intelligence indicator type is 'Botnet', 'C2', or 'Proxy', and where activity insights are available.
This rule detects successful or failed logon attempts originating from IP addresses identified by threat intelligence as associated with botnets, command and control (C2) infrastructure, or proxies. The rule specifically looks for 'LogOn' or 'FailedLogOn' activity types where the source IP's threat intelligence indicator type is 'Botnet', 'C2', or 'Proxy', and where activity insights are available.
Detects anomalous high-rate outbound network scanning activity (targeting numerous distinct destination IPs and ports) originating from internal SOHO or edge devices (e.g., Cisco, Ubiquiti, Draytek hardware). This pattern is consistent with compromised devices acting as nodes within a botnet, such as the JDY cluster, conducting reconnaissance.
Detects successful or failed logon attempts originating from IP addresses identified as associated with botnets, C2 infrastructure, or proxies by threat intelligence feeds. This indicates potential malicious activity or compromised accounts.
Detects access to botnet command and control panels
Detects successful outbound network connections to common botnet-associated remote ports (6667, 6697, 8006, 27374, 27375). The rule aggregates these connections by device to identify endpoints communicating with multiple distinct remote IP addresses, a behavior often indicative of botnet participation or command and control activity.
Detects Node.js initiating connections over port 2222. This is used by the Miasma botnet as a fallback C2/SSH channel when standard ports are blocked.
Detects Node.js initiating network connections over port 2222. This activity is associated with the Miasma botnet, which uses port 2222 as a fallback C2/SSH channel when standard ports are blocked.
Detects successful outbound network connections to common botnet-associated remote ports (6667, 6697, 8006, 27374, 27375). The rule aggregates these connections by device to identify endpoints communicating with multiple distinct remote IP addresses, a behavior often indicative of botnet participation or command and control activity.
Detects bandwidth hijacking through peer-to-peer botnet participation
Detects a device making an unusually high number of unique outbound network connections to different remote IP addresses within a short time frame (5 minutes). This behavior can indicate various malicious activities such as network scanning, botnet activity, or data exfiltration to multiple external hosts.
This rule detects network traffic indicative of a compromised host attempting to beacon to a botnet command and control server. Specifically, it looks for HTTP requests where the URI path contains "/gate.php". This pattern is commonly associated with botnet communication.
This rule detects a specific HTTP POST request pattern associated with the Mirai botnet's check-in mechanism. It looks for HTTP POST requests to the '/report' URI with a body size between 21 and 99 bytes. A threshold of 10 such requests from the same source within 60 seconds triggers the alert, indicating potential botnet activity.
Detects a device making an unusually high number of unique outbound network connections to different remote IP addresses within a short time frame (5 minutes). This behavior can indicate various malicious activities such as network scanning, botnet activity, or data exfiltration to multiple external hosts.
This detection identifies the execution of suspicious shell commands (such as download cradles, reverse shells, or unexpected GUI applications like Calculator) spawned as child processes of the Claude Code CLI ('claude'). This activity is indicative of potential Remote Code Execution (RCE) through the exploitation of malicious hooks in `.claude/settings.json` or malicious MCP server commands, as described in CVE-2025-59536.
This rule detects successful or failed logon attempts originating from IP addresses identified by threat intelligence as associated with botnets, command and control (C2) infrastructure, or proxies. The rule specifically looks for 'LogOn' or 'FailedLogOn' activity types where the source IP's threat intelligence indicator type is 'Botnet', 'C2', or 'Proxy', and where activity insights are available.
KQL Query
'The query looks for source code files being modified immediately after a build process is started. The purpose of this is to look for malicious code injection during the build process.
More details: https://techcommunity.microsoft.com/t5/azure-sentinel/monitoring-the-software-supply-chain-with-azure-sentinel/ba-p/2176463'
More details: https://techcommunity.microsoft.com/t5/azure-sentinel/monitoring-the-software-supply-chain-with-azure-sentinel/ba-p/2176463'
This query was originally published in the threat analytics report, Sysrv botnet evolution.
Sysrv is a Go-based botnet that targets both Windows and Linux servers, and steals resources to mine cryptocurrency.
The following query finds instances of remote code execution on a vulnerable Linux server.
Sysrv is a Go-based botnet that targets both Windows and Linux servers, and steals resources to mine cryptocurrency.
The following query finds instances of remote code execution on a vulnerable Linux server.
This query was originally published in the threat analytics report, Sysrv botnet evolution.
Sysrv is a Go-based botnet that targets both Windows and Linux servers, and steals resources to mine cryptocurrency.
The following query finds instances where the attacker commanded the Kinsing miner file to be downloaded on Linux devices.
Sysrv is a Go-based botnet that targets both Windows and Linux servers, and steals resources to mine cryptocurrency.
The following query finds instances where the attacker commanded the Kinsing miner file to be downloaded on Linux devices.
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