Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,154 detections
Filters
Last updated
All Time
Detection languages
683
379
342
230
173
Contributors
630
378
354
145
119
Categories
841
831
746
393
348
Platforms
1,587
586
494
263
118
Products / Services
10,683
9,759
6,695
4,421
3,750
2,154
MITRE Techniques
655
561
383
337
286
CVEs
32
20
8
7
6
IDS Classtypes
65
32
23
19
14
IDS Protocols
47
38
30
30
12
This rule monitors Cisco Unified Communications Manager (UCM) environments for multiple stages of an attack chain, including potential Server-Side Request Forgery (SSRF) attempts against administrative interfaces, suspicious file modifications by service accounts, indicators of privilege escalation, and anomalous outbound network connections from core Cisco processes.
Detects anomalous device network activity involving 5G-specific protocol ports (e.g., GTP-U, SIP). The rule aggregates unique port usage per device over 1-hour intervals to identify potential network reconnaissance, scanning, or unauthorized control plane communication.
Detects unauthenticated network connections to AutoGen Studio's Management Control Plane (MCP) WebSocket paths. AutoGen Studio's AuthMiddleware explicitly skips authentication for '/api/mcp/*' and '/api/ws/*' paths, typically on port 8081. This rule identifies attempts to access these paths without authentication, which could indicate reconnaissance or exploitation attempts against a misconfigured or vulnerable AutoGen Studio instance.
Detects signs of HTTP request smuggling attempts targeting nghttpx or similar proxies. The rule monitors for a specific poisoning precondition where an HTTP/1.1 Upgrade request contains both an 'Upgrade' header and a 'Content-Length' header, which can be leveraged to desynchronize the connection and smuggle subsequent requests (e.g., GET /poisoned).
This rule detects potentially unauthorized processes establishing network connections over port 8883 (MQTT/MQTTS) to major cloud IoT platforms (AWS IoT, Azure IoT Hub, GCP PubSub). It flags processes that are not common web browsers and calculates a suspicious score based on data volume, execution path (e.g., Temp or AppData), and the process name not matching known legitimate IoT software.
Detects HTTP traffic involving redirect chains from known Gmail URL shorteners (goo.gl, g.co, short.gy) that terminate at the identified credential-harvesting domain chongdaotang.net. This behavior is indicative of a phishing campaign designed to harvest user credentials through a multi-stage redirect.
Detects anomalous network traffic patterns characteristic of the Grandoreiro banking trojan, which tunnels Command and Control (C2) communications over STUN/WebRTC (UDP port 3478). The rule identifies processes that are not known web browsers or conferencing applications initiating these STUN connections, a technique used by the malware to blend with legitimate collaboration traffic.
Detects network connections to known malicious domains or IP addresses associated with Fortinet or Ivanti VPN phishing campaigns or command and control infrastructure. This rule identifies attempts to connect to fake VPN portals or communicate with adversary-controlled servers.
This rule detects network connections or DNS queries to known public tunneling services (e.g., Cloudflare Tunnel, localtunnel, bore, devtunnels) made by processes other than common web browsers. Attackers frequently use these services to bypass firewalls and establish unauthorized reverse shells or persistent C2 channels.
Detects anomalous device network activity involving 5G-specific protocol ports (e.g., GTP-U, SIP). The rule aggregates unique port usage per device over 1-hour intervals to identify potential network reconnaissance, scanning, or unauthorized control plane communication.
Detects potential lateral movement activity where PowerShell or the Windows Remote Management (WinRM) host process (wsmprovhost.exe) initiates network connections to multiple distinct destination IP addresses over the WinRM default ports (5985/5986). This behavior is characteristic of an adversary using legitimate remote administration tools to pivot or spread across a network.
Detects DNS queries with exceptionally long request strings (30 characters or more), which is a common indicator of DNS tunneling or command and control (C2) communication. Adversaries often encode data within the subdomain portion of a DNS query to bypass network security controls.
This rule detects pre-payload beaconing activity associated with the Meow RAT malware. It covers both network-based detection (outbound HTTP POST to known C2 domains and paths) and endpoint-based detection. Endpoint detection includes 'curl' processes communicating with known C2 infrastructure, 'osascript' processes spawned in the context of 'curl' C2 communication, and 'curl' commands using specific flags ('-k', '-s') along with a known build hash. This activity typically occurs before the main destructive payload is delivered.
Detects processes attempting to query the Cloud Instance Metadata Service (IMDS) endpoint (169.254.169.254) that are not recognized as legitimate cloud agent software (such as AWS, Azure, or Google cloud agents). This behavior is often indicative of SSRF or unauthorized discovery attempts by an adversary on a compromised cloud instance.
Detects processes attempting to query the Cloud Instance Metadata Service (IMDS) endpoint (169.254.169.254) that are not recognized as legitimate cloud agent software (such as AWS, Azure, or Google cloud agents). This behavior is often indicative of SSRF or unauthorized discovery attempts by an adversary on a compromised cloud instance.
This rule detects network connections on port 443 made to common public DNS resolvers (1.1.1.1, 8.8.8.8, 8.8.4.4, 9.9.9.9, 149.112.112.112) by processes other than known web browsers. This behavior is atypical for standard endpoint processes and may indicate the use of DNS-over-HTTPS (DoH) for command and control or data exfiltration to bypass network filtering.
Detects a single host serving materially different status codes, body sizes, or redirects to automated user agents (bots, crawlers, scanners, curl, wget, headless browsers, python, go-http) compared to normal browsers. This behavior can indicate an Adversary-in-the-Middle (AiTM) attack where the adversary is attempting to serve different content to different user agents to evade detection or deliver malicious payloads.
Identifies outbound C2 connections to domains generated by MLTBackdoor DGA.
Detects EvilTokens phishing kit gate check requests to /api/device/gate/ used to identify and burn phishing pages for security researchers
This rule detects potential cleartext leakage of usernames and passwords over FTP (port 21) by identifying HTTP requests containing common credential-related keywords in the URL, while explicitly excluding HTTPS traffic. This could indicate sensitive information being transmitted insecurely.
Detects anomalous web session traffic that proxies enterprise authorization endpoints (e.g., oauth, saml, login) while simultaneously interacting with session-related cookies. This behavior is indicative of an Adversary-in-the-Middle (AiTM) proxy setup used to capture session tokens and bypass authentication.
Page 65 of 103