Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,521 detections
Filters
Last updated
All Time
Detection languages
1,049
575
259
163
130
Contributors
536
485
323
178
133
Categories
1,256
974
852
701
406
Platforms
1,929
373
346
244
20
Products / Services
759
507
254
248
210
MITRE Techniques
18,127
15,648
12,596
8,407
6,232
2,521
CVEs
7
5
4
4
4
IDS Classtypes
201
41
5
4
1
IDS Protocols
175
38
21
9
7
Detects indicators associated with the JDY botnet targeting SOHO and IoT infrastructure. The rule monitors for suspicious firmware update attempts to non-vendor hosts, identifies high-rate outbound scanning from edge devices, and flags devices that show re-emergence of suspicious behavior after a quiet period.
Detects the execution of batch scripts that invoke file transfer utilities (certutil, bitsadmin, or powershell) to download components into temporary directories, a behavior associated with the Red Lamassu campaign.
Detects signs of JDY botnet activity on Linux systems, specifically identifying shell-based payload downloads using curl or wget, or the execution of binaries directly from temporary directories, a pattern common in IoT firmware compromises.
This rule detects suspicious command-line execution originating from common web browsers. It identifies instances where a browser process launches a command-line interpreter (cmd, powershell, or wscript) and immediately invokes known download or utility commands (curl, iwr, bitsadmin, certutil), which is a common pattern for file-less or stage-two payload delivery from malicious websites.
Detects HTTP GET requests for specific malicious archives (calculator.rar, EditorToolsPdf.zip) originating from suspected compromised Ukrainian domains (basecon.com.ua, online.zp.ua). This behavior is associated with the STOCKSTAY malware used by the threat actor Turla.
Detects anomalous HTTP GET requests targeting the ClawHub API for 'skills' that match known patterns of malicious file downloads, specifically identifying poc.py scripts or skill.md files which are indicative of the ClawHavoc campaign activity.
Detects usage of the Windows certutil.exe utility with flags commonly associated with malicious activity, including downloading files from remote URLs or decoding/encoding files within temporary or application data directories.
Detects PowerShell execution with a command line indicative of a download cradle, initiated from the user's shell (explorer.exe). This behavior is characteristic of the "ClickFix" social engineering technique where a user is tricked into copying and running a malicious command from a webpage.
Detects a sequence of events where PowerShell is used to download files from 'nvidiadriver.net' or with filenames containing 'winPatch', followed by a suspicious file drop (specifically 'winPatch.zip' or 'update.vbs') in a temporary directory within a 30-minute window. This behavior is indicative of potential initial staging for a RAT or malicious script deployment.
Detects suspicious usage of the Bun runtime, specifically when it is spawned by common Node.js development processes (like npm or node-gyp) or downloaded from non-official sources using command-line tools or browsers. This behavior is associated with the Miasma malware campaign, which abuses the Bun runtime for malicious operations.
Detects the transmission of a Metasploit Meterpreter stage over HTTP, identified by an application/octet-stream response containing the DOS MZ header signature.
Detects outbound HTTP POST requests to suspicious URIs and subsequent inbound responses containing executable binary (PE) signatures, characteristic of Emotet malware command-and-control (C2) activity.
Detects npm or node processes spawning shell interpreters (cmd.exe, powershell.exe) during package installation, which subsequently execute download utilities (curl, wget, certutil, bitsadmin). This behavior is characteristic of malicious npm packages attempting to stage payloads during the 'preinstall' or 'postinstall' hooks.
Detects the abuse of the CertUtil.exe Windows utility to download, decode, encode, or split files. This behavior is considered suspicious when initiated by common command-line shells or Office applications, which are frequently used as entry points for malicious scripts or macro-based attacks.
This rule detects instances where AutoGen Studio or related AI agents initiate potentially suspicious child processes such as command interpreters (cmd, powershell, bash) or known Living-off-the-Land Binaries (LOLBins) while simultaneously establishing outbound WebSocket connections to Model Context Protocol (MCP) endpoints. This behavior is indicative of an attacker attempting to leverage AI agent automation capabilities for code execution or remote system interaction.
This rule detects multiple outbound network connections to a specific set of known malicious C2 IP addresses on specific ports within a one-hour window. This behavior is indicative of a multi-payload delivery pattern associated with malware families such as Remcos, Agent Tesla, and RedLine.
Detects anomalous network communication patterns and file system changes indicative of SoftEther VPN usage, particularly when linked to processes masquerading as VMware or communicating with known malicious C2 infrastructure. The rule monitors for network connections on common SoftEther ports, connections to specific command-and-control IP addresses, and the creation of SoftEther configuration files like 'hamcore.se2' or 'vpn_bridge.config'.
Detects instances where the legitimate Windows utility 'Fondue.exe' (Features on Demand) loads the control panel library 'APPWIZ.cpl' from non-standard locations such as C:\Users\Public or AppData directories. It also identifies the staging phase where 'APPWIZ.cpl' is written to 'C:\Users\Public', which is indicative of a DLL side-loading attack sequence, often associated with the Elephant malware dropper.
This rule detects network communication to a known command and control (C2) server (23.254.164.123:443) associated with the 'protocal.cjs' backdoor, which is part of the 'easy-day-js' npm supply chain compromise. The detection specifically looks for TLS traffic with a Server Name Indication (SNI) and general IP traffic to this C2 address.
Detects Node.js processes engaging in suspicious behaviors related to supply chain or second-stage attacks. This includes executing scripts from hidden .peer/ directories, accessing specific staging script filenames, and performing DNS requests or network connections to the known malicious domain data-stream.space.
Detects HTTP GET requests to a specific self-hosted GitLab domain 'gitlab.bzctoons.net' that attempt to download a file named 'protected.zip', which is associated with the retrieval of StealC information-stealing malware by the Amadey loader.
Page 65 of 121