Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
653 detections
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Detects high-frequency requests for 'tools/list' from a single source IP across multiple unique destination hosts. This pattern is indicative of a breadth-first scan attempting to identify reachable Model Context Protocol (MCP) servers, rather than typical legitimate client-to-server communication.
This rule monitors for internal network connection attempts initiated by the 'mcp-grafana' process to destinations it has not contacted in the previous 14 days. By establishing a baseline of legitimate data source connections, the rule alerts when the process performs a rapid fan-out or discovery against multiple new internal hosts, which may indicate unauthorized network reconnaissance or lateral movement attempts by the Grafana service.
This rule monitors for active reconnaissance or scanning behavior by detecting a single source IP interacting with a high number of distinct ports/hosts within a short time frame (NetworkScan) or accessing a high number of distinct URI paths/404 errors (WebContentScan).
This rule monitors web server logs (IIS, W3C, and Azure Application Gateway) for incoming traffic that matches known malicious or automated vulnerability scanners, as well as requests for common system fingerprinting paths (such as /server-status or /.git/config). The rule aggregates these hits by source IP address to identify potential active reconnaissance or vulnerability scanning attempts.
Detects high-frequency TCP/445 connection attempts (a 'connect sweep') characteristic of automated SMB share enumeration, which is commonly used for lateral movement reconnaissance. The rule triggers when a threshold of 40 connection requests occurs from a single source within a 30-second window, specifically targeting SMB-related lateral movement behaviors.
Detects automated directory fuzzing attempts against Azure Storage blobs targeting sensitive files like .env, .pem, or configuration files. The rule identifies suspicious activity by aggregating requests from Anonymous or SAS-authenticated sources that exhibit high request volumes and access to multiple distinct sensitive paths, while excluding known legitimate bulk-transfer and synchronization tools.
Detects automated directory fuzzing attempts against Azure Storage blobs targeting sensitive files like .env, .pem, or configuration files. The rule identifies suspicious activity by aggregating requests from Anonymous or SAS-authenticated sources that exhibit high request volumes and access to multiple distinct sensitive paths, while excluding known legitimate bulk-transfer and synchronization tools.
Detects automated directory fuzzing attempts against Azure Storage blobs targeting sensitive files like .env, .pem, or configuration files. The rule identifies suspicious activity by aggregating requests from Anonymous or SAS-authenticated sources that exhibit high request volumes and access to multiple distinct sensitive paths, while excluding known legitimate bulk-transfer and synchronization tools.
Detects automated reconnaissance and enumeration of sensitive web application paths (admin, config, environment files, etc.) from a single source IP. The rule identifies high-frequency request patterns that target specific non-public surface areas while excluding known search engine crawlers and monitoring bots.
Detects automated reconnaissance and enumeration of sensitive web application paths (admin, config, environment files, etc.) from a single source IP. The rule identifies high-frequency request patterns that target specific non-public surface areas while excluding known search engine crawlers and monitoring bots.
Detects high-rate scanning and automated service probing patterns consistent with network reconnaissance. This includes tracking TCP SYN floods to external segments, excessive HTTP/login requests, and automated fingerprinting probes (e.g., favicon or admin panel enumeration). The rule accounts for common uptime monitoring services to minimize false positives.
Detects high-rate scanning and automated service probing patterns consistent with network reconnaissance. This includes tracking TCP SYN floods to external segments, excessive HTTP/login requests, and automated fingerprinting probes (e.g., favicon or admin panel enumeration). The rule accounts for common uptime monitoring services to minimize false positives.
Detects high-velocity, automated web activity originating from a single source IP that simultaneously performs widespread endpoint enumeration, tests sensitive authentication flows, and attempts common injection attack payloads. This behavior is indicative of an automated scanner, crawler, or malicious botnet agent performing rapid discovery and exploitation attempts.
Detects high-velocity, automated web activity originating from a single source IP that simultaneously performs widespread endpoint enumeration, tests sensitive authentication flows, and attempts common injection attack payloads. This behavior is indicative of an automated scanner, crawler, or malicious botnet agent performing rapid discovery and exploitation attempts.
Detects high-velocity, automated web activity originating from a single source IP that simultaneously performs widespread endpoint enumeration, tests sensitive authentication flows, and attempts common injection attack payloads. This behavior is indicative of an automated scanner, crawler, or malicious botnet agent performing rapid discovery and exploitation attempts.
Detects repeated HTTP requests targeting the '/cgi-bin/' path on Dahua camera web interfaces with a specific user-agent string ('CGI Brute'). This behavior is characteristic of an automated brute-force campaign attempting to gain unauthorized access to camera web administration interfaces.
This rule detects rapid SYN packet patterns from external sources targeting the Dahua proprietary port 37777, characteristic of network scanning tools like Masscan attempting to discover or identify vulnerable Dahua devices.
Detects usage of the 'finger' utility via command line within scripts or batch files, or network connections originating from the 'finger' process on port 79 to non-internal destinations. This activity is commonly associated with internal network reconnaissance to gather user information or system details.
Detects usage of the 'finger' utility via command line within scripts or batch files, or network connections originating from the 'finger' process on port 79 to non-internal destinations. This activity is commonly associated with internal network reconnaissance to gather user information or system details.
This rule monitors network traffic from internal devices and security logs for communication with a curated list of known malicious or suspicious scanner IP addresses, indicating potential reconnaissance or probing activity by external actors.
This rule detects rapid, repetitive connection attempts (TCP SYN) from a source within the internal network to a set of high-value targets (SSH, HTTP, SMB, RDP ports) within the same internal network. Such patterns are indicative of lateral movement or internal network reconnaissance, often performed by adversaries pivoting through a compromised host to discover services on other internal systems.
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