Detections

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

3,989 detections

Detects network connections or DNS queries to known suspicious domains associated with command and control infrastructure.
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Ankit Mehta@Secvyn
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SlimKQL
1 month ago
002
Detects network connections or DNS queries to known suspicious domains associated with command and control infrastructure.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
102
Detects suspicious file activity where a script or process creates a staging folder within 'C:\Users\Public\' and subsequently writes potential decoy PDF files or compressed archive payloads to that same directory. This behavior is indicative of a dropper or secondary stage malware delivery mechanism utilizing world-writable directories for staging.
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Subhankar H@Andrewsec57
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Detections.ai Community
1 month ago
103
Detects network connections, process command line arguments, and DNS queries associated with identified Galago or Panzer ransomware C2, leak site, or contact infrastructure (Tox IDs/Tor .onion addresses).
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Ankit Mehta@Secvyn
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Detection & Hunting Community
1 month ago
002
Detects network connections, process command line arguments, and DNS queries associated with identified Galago or Panzer ransomware C2, leak site, or contact infrastructure (Tox IDs/Tor .onion addresses).
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
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Arnold Chan@slaz
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Midnight Slayer
1 month ago
102
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
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Arnold Chan@slaz
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Detection & Hunting Community
1 month ago
002
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
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Arnold Chan@slaz
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Hunters
1 month ago
102
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
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Arnold Chan@slaz
Defender - KQL
1 month ago
002
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
202
This rule detects DNS queries or network connections originating from endpoints to a list of known malicious domains associated with various malware families (ClearFake, IClickFix, AMOS, Vidar, etc.). This helps identify potential C2 communication, malicious payload delivery, or infrastructure interaction.
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Ankit Mehta@Secvyn
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SlimKQL 2026
2 months ago
12023
Detects anomalous network traffic patterns from 'rnpkeys.exe', a known loader associated with the Sauron malware, communicating with predefined command-and-control (C2) domains or over HTTPS. The rule identifies high volumes of short-lived, frequent connections indicative of fragmented exfiltration (e.g., screenshots) blended into regular beaconing activity.
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Ankit Mehta@Secvyn
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SlimKQL
1 month ago
101
Detects anomalous network traffic patterns from 'rnpkeys.exe', a known loader associated with the Sauron malware, communicating with predefined command-and-control (C2) domains or over HTTPS. The rule identifies high volumes of short-lived, frequent connections indicative of fragmented exfiltration (e.g., screenshots) blended into regular beaconing activity.
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Ankit Mehta@Secvyn
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Hunters
1 month ago
001
Detects anomalous network traffic patterns from 'rnpkeys.exe', a known loader associated with the Sauron malware, communicating with predefined command-and-control (C2) domains or over HTTPS. The rule identifies high volumes of short-lived, frequent connections indicative of fragmented exfiltration (e.g., screenshots) blended into regular beaconing activity.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
001
Detects anomalous network behavior consistent with the PolinRider malware, which uses public Ethereum JSON-RPC endpoints and blockchain explorers (e.g., Etherscan.io) as a dead-drop resolver for command-and-control (C2) communication. The rules monitor for specific RPC methods (eth_getTransactionByHash, eth_call, eth_getBalance) over HTTP/TLS and DNS resolution queries to known blockchain explorer infrastructure.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
005
Detects network activity associated with NetSupport Manager remote access software, specifically monitoring for connections to known malicious domains and infrastructure, as well as recurring beaconing patterns indicative of command-and-control behavior.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
005
Detects network communication to a known malicious IP address (45.32.253.166) associated with the PIVOTPIPE RAT using Cobalt Strike C2 beaconing patterns. The rule identifies TCP connections, HTTP GET requests for beacon check-ins, and HTTP POST requests for task responses.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
005
This rule detects network communication to known malicious IP addresses or sessions utilizing TLS certificates that impersonate the Uzbekistan railway authority (azure.uzrailwaystax). This behavior is characteristic of the SpiceRAT/NodeEdgeRAT malware families, which use these specific certificates to establish Command and Control (C2) channels.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
106
Detects network connection attempts to 'third-party.com', which was historically a common documentation placeholder domain but has since been acquired by attackers to serve malicious infrastructure. This rule flags processes interacting with this domain, identifying potential exploitation via copy-pasted code or documentation examples.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
102
Detects network connections originating from or connecting to hosts that utilize known Cobalt Strike default JA3 or JA3S TLS fingerprints. These fingerprints are indicative of Cobalt Strike's default beacon communication patterns.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
002
Detects outbound network connections to a known malicious IP address (45.94.31.112) associated with C2 beaconing. The rule identifies communication directed to specific API endpoints (/api/v3/r, /api/v3/s) originating from processes other than common web browsers, suggesting the use of dedicated beaconing or malware agents (e.g., direct WinHTTP usage).
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Ankit Mehta@Secvyn
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Detection & Hunting Community
1 month ago
002
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