Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects anomalous activity originating from AutoGen Studio AI agents, specifically identifying attempts to abuse loopback trust boundaries via MCP (Model Context Protocol) WebSocket requests to localhost (ports 8080/8081) or the execution of suspicious child processes commonly used for command-line interference, indicative of AI agent compromise or attacker-controlled MCP command injection.
Detects the obfuscated 'setup.cjs' dropper associated with the easy-day-js npm supply chain attack. The rule identifies unique obfuscated variable names, XOR-encoded marker bytes, and specific campaign-related strings, including postinstall commands, package names, second-stage payload filenames, self-deletion patterns, and TLS bypass indicators.
Detects high-volume file modification or renaming operations targeted at specific file extensions (dcm, tf, parquet) commonly associated with sensitive data (DICOM imaging, Terraform states, database parquet files) or operations occurring within Docker volume directories. The detection uses an aggregation logic to identify when a process performs more than 20 such file operations on an endpoint, which may indicate bulk data exfiltration, encryption, or tampering.
This rule detects attempts by common scripting or utility processes (like osascript, curl, zsh, bash, sh, python) to access sensitive macOS files, specifically targeting browser data (Chrome, Brave, Firefox) and keychain files. This activity could indicate an attacker attempting to exfiltrate credentials, session tokens, or other sensitive user data.
Detects outbound network connections from devices to known FortiBleed command and control (C2) servers and sniffer infrastructure IP addresses. This rule helps identify potential compromises involving the FortiBleed vulnerability exploitation.
This rule detects potential command and control (C2) beaconing activity by identifying devices communicating with known suspicious remote IP addresses at regular, repeating intervals. It calculates the time difference between consecutive connections to specific suspicious IPs and identifies devices that establish at least three connections within one-hour bins, adhering to a 1 to 15-minute heartbeat interval.
Detects anomalous authentication patterns where a single source IP address exhibits multiple failed login attempts followed by at least one successful login within a 10-minute time window, indicative of credential stuffing or password spraying.
Detects user-initiated Terminal execution of a ClickFix bash payload copied from a fake CAPTCHA page. The command uses mktemp to create a /tmp DMG, downloads it via curl -fsSL from svs-verificationdate.beer, then silently mounts it with hdiutil attach -nobrowse to deliver the Atomic macOS Stealer (AMOS).
Detects unauthorized processes attempting to access or perform operations on sensitive files such as browser credentials, SSH keys, crypto wallets, and password manager databases. The rule specifically looks for non-standard or unsigned processes interacting with a high volume of these files in a short time frame, which is indicative of credential harvesting by infostealer malware like Lumma, Redline, or Vidar.
Detects DNS queries for known StegoAd command-and-control infrastructure domains, which are used as proxy relays and exfiltration endpoints.
This rule detects network connections from internal hosts to a list of known malicious IP addresses associated with the Payroll Pirate campaign (attributed to Storm-2755 and Storm-2657). Identifying these connections indicates potential communication with adversary-controlled infrastructure.
Detects the installation of Visual Studio Code extensions from sources other than the official Marketplace. This activity is monitored by checking process command line arguments for the --install-extension flag combined with external URLs or local file paths, which may indicate an attempt to install malicious extensions.
Detects network communication to the malicious domain 'mitarchive.info' from common web browsers (Chrome, Edge, Firefox, Brave). This domain is associated with the StegoAd browser extension, which intercepts Google and WordPress login flows to exfiltrate stolen credentials and 2FA codes.
Detects suspicious or unexpected child processes spawned from a Ghidra JVM environment. This rule is designed to monitor for potential Remote Code Execution (RCE) or Arbitrary Code Execution (ACE) attempts targeting Ghidra, where the application environment is abused to launch system shells, interpreters, or common attacker tools.
Detects file creation or modification events associated with the known malicious Chromium extension 'Search for perplexity ai' (ID: flkebkiofojicogddingbdmcmkpbplcd). The rule monitors for the installation of the extension and the creation of its declarativeNetRequest rule files (perplexity-rules.json, bing-rules.json, google-rules.json), which are used to hijack browser search queries and redirect them to a typosquatted domain.
This rule detects network connections to specific deep link patterns associated with messaging applications like Telegram, WhatsApp, and Signal. Such deep links can be used in phishing attempts or to initiate actions on a user's device through these applications.
This rule detects a high volume of UDP network connections originating from a single process on a device. A count exceeding 50 UDP connections from the same process to the same remote IP address is considered anomalous and could indicate a UDP flood or other denial-of-service attempt.
Detects the use of npm to install known malicious npm packages, which is indicative of a supply chain compromise attempt via typosquatting or malicious dependency injection.
This rule detects instances where the Ghidra reverse engineering suite (or associated Java processes running Ghidra components) initiates suspicious child processes. This behavior is considered anomalous as standard reverse engineering activities in Ghidra should not require the execution of system administrative tools, interpreters, or networking utilities, which may indicate an attacker using a compromised development environment to launch secondary payloads or tools.
This rule identifies potential ransomware activity by detecting a process performing a high volume of file rename or modification operations within a short time window. It specifically targets files with known ransomware extensions or those using randomized 6-8 character alphanumeric extensions, while excluding common administrative, backup, and temporary file operations performed by trusted software.
Detects network and process execution activity involving Google or Microsoft OAuth2 token endpoints from non-browser and non-trusted processes. This behavior is indicative of potential token theft or session hijacking attempts, where malicious tools (e.g., curl, python) are used to access authentication endpoints to bypass standard user interaction.
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