Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

2,309 detections

Detects NeedyMantis' WebSockets comms-module handshake: an outbound HTTP GET to port 443 whose User-Agent is EXACTLY the hard-coded literal 'firefox/21.0' (anchored start+end, not a substring of a real browser UA) AND whose headers contain an explicit 'Upgrade: websocket' value. Anchoring the UA to an exact match and requiring the literal upgrade header (rather than just the presence of an 'Upgrade' header name) removes legitimate WebSocket apps and any app whose real UA merely contains 'firefox/21.0' as a substring.
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Arnold Chan@slaz
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Detection & Hunting Community
1 month ago
001
Detects NeedyMantis' WebSockets comms-module handshake: an outbound HTTP GET to port 443 whose User-Agent is EXACTLY the hard-coded literal 'firefox/21.0' (anchored start+end, not a substring of a real browser UA) AND whose headers contain an explicit 'Upgrade: websocket' value. Anchoring the UA to an exact match and requiring the literal upgrade header (rather than just the presence of an 'Upgrade' header name) removes legitimate WebSocket apps and any app whose real UA merely contains 'firefox/21.0' as a substring.
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Arnold Chan@slaz
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Midnight Slayer
1 month ago
001
Detects NeedyMantis' WebSockets comms-module handshake: an outbound HTTP GET to port 443 whose User-Agent is EXACTLY the hard-coded literal 'firefox/21.0' (anchored start+end, not a substring of a real browser UA) AND whose headers contain an explicit 'Upgrade: websocket' value. Anchoring the UA to an exact match and requiring the literal upgrade header (rather than just the presence of an 'Upgrade' header name) removes legitimate WebSocket apps and any app whose real UA merely contains 'firefox/21.0' as a substring.
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Arnold Chan@slaz
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Hunters
1 month ago
001
Detects NeedyMantis' WebSockets comms-module handshake: an outbound HTTP GET to port 443 whose User-Agent is EXACTLY the hard-coded literal 'firefox/21.0' (anchored start+end, not a substring of a real browser UA) AND whose headers contain an explicit 'Upgrade: websocket' value. Anchoring the UA to an exact match and requiring the literal upgrade header (rather than just the presence of an 'Upgrade' header name) removes legitimate WebSocket apps and any app whose real UA merely contains 'firefox/21.0' as a substring.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
001
This rule detects HTTP requests where the User-Agent header indicates a PowerShell execution occurring from a system configured with the zh-CN locale. This pattern is often associated with automated scripts or potential malicious activity masquerading as legitimate PowerShell traffic.
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Ibrahim Saud@tektrix
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Detections.ai Community
30 days ago
000
Detection of common web server reconnaissance, enumeration, and brute-force patterns targeting IIS environments. This includes detection of short-name (~1) probes, WebDAV method usage, NTFS alternate data stream requests, and brute-force attempts on login endpoints originating from PowerShell user agents.
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Ibrahim Saud@tektrix
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Detections.ai Community
30 days ago
000
Detects network activity (DNS, TLS, HTTP) associated with suspected C2 infrastructure hosted on Cloudflare Workers, specifically identifying patterns consistent with trojanized authentication pages acting as browser-based C2 relays or WebRTC/WebSocket signaling channels.
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Ibrahim Saud@tektrix
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Detections.ai Community
30 days ago
000
Detects two-stage communication pattern used by the Lorem Ipsum Loader. The first stage involves a GET request to a specific host acting as a dead-drop resolver to retrieve configuration. The second stage involves a POST request to an external destination containing a JPEG file header, characteristic of image-based C2 traffic.
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Ibrahim Saud@tektrix
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Detections.ai Community
30 days ago
000
This rule detects DNS queries, TLS SNI, and HTTP requests to a list of known malicious domains associated with the STAC4924 threat activity, specifically linked to the TerminalFix or Lorem Ipsum Loader malware.
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Ibrahim Saud@tektrix
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Detections.ai Community
30 days ago
000
Detects outbound HTTP requests from endpoints to a known C2 infrastructure associated with mobile device spyware. The rule identifies two specific stages: polling for new commands using a GET request and posting command execution results using a POST request, both targeting an MDM-mimicking API structure.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
003
This rule monitors for outbound TCP and HTTP traffic to a known malicious infrastructure hosting a fake or compromised 'Corp MDM' (Mobile Device Management) admin panel, which serves as a Command and Control (C2) channel for spyware.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
003
Detects an Android device registration attempt to a known malicious C2 IP address using parameters characteristic of a mobile device management (MDM) implant. The rule looks for a POST request to a specific registration endpoint containing device identifiers like deviceId, manufacturer, model, and osVersion.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
003
Detects specific C2 communication patterns associated with SCKIT, including HTTPS beaconing to the skyleen.fr domain and structured URI patterns used for configuration and status requests.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
005
Detects HTTP GET requests targeting the Vite Dev Server that include directory traversal sequences ('../') within the '/@fs/' endpoint. This pattern is indicative of an attempt to bypass root directory restrictions to access sensitive files on the server.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
103
Detects repeated attempts to enumerate available model endpoints on a LiteLLM server, a behavior often associated with reconnaissance targeting AI gateway services to identify exposed models.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
003
Detects anomalous POST requests to Citrix NetScaler SAML authentication endpoints (/saml/login or /cgi/samlauth) that result in an HTTP 500 error, which may indicate a heap overflow exploitation attempt associated with CVE-2026-8452.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
203
Detects HTTP POST requests directed at common LLM API endpoints (chat completions, model beta) that contain patterns indicative of LLM prompt injection or malicious code generation requests, such as commands for code obfuscation or payload regeneration, specifically where the User-Agent does not match standard browser strings and the request body contains base64 encoded instructions.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
This rule detects HTTP POST requests from mobile user agents (Android, Dalvik, okhttp) that contain keywords indicative of contactless payment card data exfiltration, specifically looking for fields such as 'track2', 'pan', 'atc', and 'cryptogram'. This behavior is consistent with malicious mobile applications attempting to transmit skimmed NFC credit card data to an external server.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
Detects network traffic associated with the XWorm v7.4 Remote Access Trojan (RAT) encrypted plugin C2 channel. The rule monitors for a specific hex pattern ('58 57') at the beginning of TCP payloads directed to known non-standard ports (7000, 8808, 9999) with a payload size constraint, indicating potential command-and-control communication.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
This rule detects inbound HTTP requests targeting Oracle PeopleSoft applications that contain malicious patterns indicative of Server-Side Request Forgery (SSRF) attempts. The rule inspects the URI for specific PeopleSoft application paths and suspicious redirection or internal IP address patterns (including internal cloud metadata addresses like 169.254.169.254) which are commonly used in SSRF attacks to probe or access internal resources.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
Detects outbound HTTP PUT requests characteristic of data exfiltration associated with Qilin ransomware. The rule monitors for the use of command-line tools like s5cmd or rclone for uploading data, often used during the double extortion phase where stolen data is uploaded to leak sites.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
202
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