Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,303 detections
Filters
Last updated
All Time
Detection languages
2,251
22
21
7
2
Contributors
910
584
506
125
48
Categories
20,424
11,812
5,870
5,145
4,864
2,303
Platforms
2,190
209
168
62
61
Products / Services
2,250
2,159
163
32
31
MITRE Techniques
713
422
384
187
184
CVEs
17
12
12
12
10
IDS Classtypes
995
426
281
190
98
IDS Protocols
1,291
401
281
117
45
This rule detects potential exploitation attempts against SonicWall SMA1000 appliances, specifically targeting the /wsproxy endpoint using a custom 'SMA Connect Agent' user agent string. This behavior is associated with SSRF vulnerabilities (CVE-2026-15409 and CVE-2026-15410) identified as being utilized by the threat actor group UTA0533 in campaigns involving INC Ransomware.
This rule detects periodic network beaconing patterns consistent with BabylonRAT malware. It flags established TCP connections to external networks that occur at a frequency exceeding 5 connections within a 300-second window, which may indicate a C2 check-in mechanism. Due to the heuristic nature of this detection, it is recommended to tune the threshold and correlate with payload analysis or entropy inspection to reduce noise.
This rule detects periodic network beaconing patterns consistent with BabylonRAT malware. It flags established TCP connections to external networks that occur at a frequency exceeding 5 connections within a 300-second window, which may indicate a C2 check-in mechanism. Due to the heuristic nature of this detection, it is recommended to tune the threshold and correlate with payload analysis or entropy inspection to reduce noise.
Detects command-and-control (C2) communication patterns associated with the Graphalgo framework, which utilizes the Arbitrum Sepolia blockchain for dead-drop resolution and task orchestration. The rules monitor for specific JSON-RPC method calls ('eth_call', 'setCPubKey') and repeated polling of contract functions ('serviceData') characteristic of this threat actor's network behavior.
Detects network activity associated with the DarkMe RAT, including DNS lookups for its known C2 domain 'thatawful.boutique' and outbound TCP connections to a hardcoded non-standard port (7712) at a known malicious C2 IP address.
This rule detects outbound network communications (TLS, MQTT, and HTTP) to HiveMQ infrastructure. The pattern of activity suggests the presence of 'Bird Agent' malware utilizing the MQTT protocol for command and control (C2) communication, as well as periodic HTTP beaconing to HiveMQ broker endpoints.
Detects outbound TCP traffic from the internal network to external destinations that match characteristics of Gorilla RAT registration beacons. This includes established sessions with small packet sizes (<64 bytes) and frequent, repeated attempts as defined by the threshold.
Detects high-volume HTTP GET requests containing the 'SetupCompleted' URI pattern directed at PaperCut servers, which is indicative of automated exploitation attempts targeting authentication bypass vulnerabilities.
Detects network traffic consistent with automated penetration testing frameworks such as Nuclei, ffuf, or sqlmap. This rule monitors HTTP user-agent strings and triggers an alert if high-frequency scanning activity from a single source is observed within a 60-second window, which is indicative of automated reconnaissance or vulnerability scanning.
Detects attempts to exploit the Langflow 'validate/code' endpoint, which is associated with CVE-2025-3248. The rule monitors HTTP POST requests to this endpoint for specific character patterns within the request body, indicative of malicious payloads attempting to achieve code execution.
Detects repeated HTTP POST requests containing 'ScreenConnect' in the URI, originating from external networks. This pattern is indicative of automated scanning activity attempting to exploit potential authentication bypass or session hijacking vulnerabilities (such as CVE-2026-84869) in ConnectWise ScreenConnect instances.
Detects an attempt to exploit CVE-2025-3248, an unauthenticated remote code execution vulnerability in Langflow. The rule identifies POST requests to the '/api/v1/validate/code' endpoint that contain base64 encoded strings in the request body, which are characteristic of malicious Python payloads designed to execute arbitrary code.
This rule detects network traffic indicative of N0va Phishkit verification or session initialization. It looks for specific GET request URI parameters (/api/verification/init?session=, flow=, prompt_profile=) that align with the initial handshake phase of this phishing kit, which is often used for credential and session cookie theft.
This rule detects network traffic indicative of N0va Phishkit verification or session initialization. It looks for specific GET request URI parameters (/api/verification/init?session=, flow=, prompt_profile=) that align with the initial handshake phase of this phishing kit, which is often used for credential and session cookie theft.
Detects anomalous MS_T120 channel binding and MCS handshake patterns characteristic of the BlueKeep (CVE-2019-0708) remote code execution vulnerability in Microsoft RDP services.
Detection rules identifying malformed RDP MCS Connect Initial PDUs and unusual service crashes following RDP connection attempts, both indicative of exploitation attempts against the CVE-2019-0708 (BlueKeep) vulnerability.
Detection rules identifying malformed RDP MCS Connect Initial PDUs and unusual service crashes following RDP connection attempts, both indicative of exploitation attempts against the CVE-2019-0708 (BlueKeep) vulnerability.
Detects specific malformed HTTP request patterns associated with the Casbaneiro (Metamorfo) banking trojan. The rules identify suspicious beaconing attempts, including specific URI structures ('/$p', '/$or?u=') and malformed headers (missing Host header combined with specific Content-Length anomalies).
This rule detects network traffic originating from potential Casbaneiro or Ousaban malware that uses HTTP 302 redirects to redirect non-targeted IP addresses to Google or YouTube. This behavior is used as a geofencing and sandbox evasion technique to prevent security analysts and automated systems from seeing the actual malicious payload.
This rule detects network traffic patterns associated with the Koktevrat Android RAT, specifically identifying periodic TLS beacons (heartbeats) destined for known C2 domains (streams-tv.lol and stream-plus.lat). The behavior suggests the use of Android's AlarmManager to schedule recurring callbacks to the C2 infrastructure.
This rule detects potential command and control (C2) activity associated with the Koktevrat malware, specifically looking for WebSocket handshake requests (HTTP GET with 'Upgrade' header) to domain names that follow a generated pattern (8-27 alphanumeric characters ending in .icu or .cfd).
Page 49 of 110


