Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
228 detections
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Detects network activity related to the exploitation of the CVE-2025-31702 vulnerability in Dahua P2P Relay services. The rules monitor for probe attempts, device parameter fetching (randsalt), serial number enumeration bursts, and successful no-auth channel responses, indicating a bypass of authentication mechanisms on vulnerable Dahua devices.
Detects incoming HTTP requests where the 'pagename' parameter contains directory traversal sequences (e.g., '../', '..%2f'). These attempts are typically indicative of automated vulnerability scanning or exploitation attempts targeting WordPress page-template resolution logic, specifically related to CVE-2026-87902.
Detects high-frequency, unauthenticated Redis PING/AUTH attempts indicative of a reconnaissance scan against the Redis service. This activity typically represents an adversary performing mass fingerprinting or attempting to identify unsecured Redis instances.
This rule monitors for the execution of common penetration testing tools (nuclei, ffuf, sqlmap) and detects network activity towards OpenRouter.ai, a platform that provides access to various Large Language Models (LLMs), often used in automation or script-assisted reconnaissance and exploitation. It also flags instances where container runtimes are used to execute these same tools.
Detects anomalous, high-frequency, multi-channel probing of AI agent input surfaces. The rule identifies external actors sending instruction-injection style keywords across different communication channels (e.g., email, Teams, calendar) within a short window, which may indicate an attempt to identify and manipulate an organization's autonomous agents. Covers T1595.002
Detects anomalous, high-frequency, multi-channel probing of AI agent input surfaces. The rule identifies external actors sending instruction-injection style keywords across different communication channels (e.g., email, Teams, calendar) within a short window, which may indicate an attempt to identify and manipulate an organization's autonomous agents. Covers T1595.002
Detects anomalous, high-frequency, multi-channel probing of AI agent input surfaces. The rule identifies external actors sending instruction-injection style keywords across different communication channels (e.g., email, Teams, calendar) within a short window, which may indicate an attempt to identify and manipulate an organization's autonomous agents. Covers T1595.002
This rule detects potential automated reconnaissance activity characteristic of the 'Strix' tool against web applications. It uses two detection mechanisms: tracking high-frequency requests that match typical scanning path patterns (excluding OPTIONS requests) and monitoring for a surge in 404 or 400 error responses, which often indicates an automated vulnerability scanner attempting to probe non-existent resources.
Detects a multi-stage attack pattern against publicly exposed AI service endpoints. The detection correlates: (1) Enumeration of sensitive AI/MCP-related API endpoints (minimum 3 distinct hits) in a 10-minute window; (2) Subsequent POST requests to AI service endpoints within 15 minutes of the enumeration; and (3) A spike of 5 or more server errors (HTTP 5xx) within 10 minutes following the POST activity. This pattern suggests automated reconnaissance followed by attempted exploitation of exposed AI model interfaces or orchestration services. Covers T1595.002, T1190
Detects a multi-stage attack pattern against publicly exposed AI service endpoints. The detection correlates: (1) Enumeration of sensitive AI/MCP-related API endpoints (minimum 3 distinct hits) in a 10-minute window; (2) Subsequent POST requests to AI service endpoints within 15 minutes of the enumeration; and (3) A spike of 5 or more server errors (HTTP 5xx) within 10 minutes following the POST activity. This pattern suggests automated reconnaissance followed by attempted exploitation of exposed AI model interfaces or orchestration services. Covers T1595.002, T1190
Detects a multi-stage attack pattern against publicly exposed AI service endpoints. The detection correlates: (1) Enumeration of sensitive AI/MCP-related API endpoints (minimum 3 distinct hits) in a 10-minute window; (2) Subsequent POST requests to AI service endpoints within 15 minutes of the enumeration; and (3) A spike of 5 or more server errors (HTTP 5xx) within 10 minutes following the POST activity. This pattern suggests automated reconnaissance followed by attempted exploitation of exposed AI model interfaces or orchestration services. Covers T1595.002, T1190
Detects high-frequency TCP SYN packet bursts targeting port 37777 (commonly used by Dahua surveillance devices). The detection triggers when more than 50 SYN packets from a single source are observed within a 10-second window, suggesting automated reconnaissance or vulnerability scanning activity.
This rule detects suspicious UDP traffic directed at port 8800 targeting the Dahua P2P cloud relay interface. It specifically monitors for enumeration attempts against device serial numbers, which may be a precursor to unauthorized access or reconnaissance against vulnerable Dahua devices.
This rule identifies IoT devices that have reported critical or high severity software vulnerabilities within the last 24 hours. It correlates DeviceTvmSoftwareVulnerabilities data with DeviceInfo to specifically isolate vulnerable IoT-categorized assets and provides a summary of affected devices, software, and the associated CVEs to prioritize remediation efforts.
Detects high-frequency connection attempts to PPTP (1723) and L2TP (1701) VPN ports from an external source, indicative of automated scanning or vulnerability discovery activity.
This rule detects high-frequency TCP SYN connection attempts originating from external networks targeting common administrative or tunneling ports (1723/PPTP, 1701/L2TP, 22/SSH) on internal systems. The detection uses a threshold of 100 connection attempts within 120 seconds, which is characteristic of automated reconnaissance and network scanning behavior.
This rule identifies instances of the Acronis backup plugin for cPanel, WHM, or Plesk running on versions older than 1.9.3 HF3. This versioning threshold corresponds to the patch level required to mitigate the security vulnerability identified as CVE-2026-87886.
Detects incoming HTTP GET requests targeting Vite development server environments that utilize suspicious query parameters typically associated with vulnerability exploitation (e.g., directory traversal or sensitive file access). The rule specifically flags requests where the User-Agent string contains bot keywords but excludes verified IP ranges, suggesting an attempt to bypass security filters by spoofing crawler identities.
Detects incoming HTTP GET requests targeting Vite development server environments that utilize suspicious query parameters typically associated with vulnerability exploitation (e.g., directory traversal or sensitive file access). The rule specifically flags requests where the User-Agent string contains bot keywords but excludes verified IP ranges, suggesting an attempt to bypass security filters by spoofing crawler identities.
Detects high-volume bursts of HTTP GET requests against specific paths associated with a Vite development server (/@vite/client, /@fs/, /src/) on port 5173. This pattern is indicative of automated reconnaissance or vulnerability scanning targeting an exposed development environment.
Detects high-frequency connection attempts to PPTP (1723) and L2TP (1701) VPN ports from an external source, indicative of automated scanning or vulnerability discovery activity.
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