Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects Python scripts making outbound network connections directly to IP addresses without prior DNS resolution. This behavior can strongly indicate hardcoded Command and Control (C2) communication, where an adversary has embedded the C2 server's IP address directly into the script to bypass DNS-based security controls or to ensure connectivity even if DNS is compromised or unavailable. The rule filters out private IP addresses and aggregates connections by device and remote IP, flagging those with a low connection count (less than 10) to reduce noise from legitimate, high-volume bare-IP traffic.
Detects the removal of known Amos Stealer staging artifacts, specifically the 'osalogging.zip' file or 'sync' directories within the /tmp folder. This behavior indicates post-exfiltration cleanup to evade detection.
Detects the use of curl with specific command-line flags (-kfsSL) commonly used by Amos Stealer to silently download its initial payload, bypassing TLS warnings and hiding output. This behavior is indicative of an adversary attempting to transfer tools or malware onto a system without user interaction or visible output.
This rule detects attempts to clean up artifacts associated with the Amos Stealer by monitoring for the deletion of known staging paths. Specifically, it looks for the execution of 'rm' commands targeting '/tmp/osalogging.zip' or '/tmp/sync'. This activity suggests an adversary is trying to remove traces of their presence after data exfiltration or staging.
Detects the execution of 'curl' with specific flags ('-kfsSL') often used for silent and insecure file downloads. This pattern has been observed in malware like Amos Stealer to download malicious payloads. The rule looks for 'curl' as the filename or at the beginning of the command line, combined with the specified flags and an HTTP/HTTPS URL.
This rule detects the creation of files with names commonly associated with ransomware notes (e.g., 'ransom_note', 'decrypt_files', 'pay_ransom') and common text file extensions (.txt, .html, .htm). It summarizes these events by device and time, flagging devices where at least one such file is observed.
Detects command-line installation of VS Code extensions (.vsix) launched by script interpreters. Threat actors like UNK_DeadDrop use this technique to silently install malicious extensions via VBScript and CMD payloads.
Detects the creation or modification of VS Code tasks.json files outside of normal IDE or version control operations. Threat actors, such as North Korean groups, are weaponizing the "runOn: folderOpen" feature in tasks.json for auto-execution when a cloned repository is opened.
Identifies the payload invoking the native macOS security command-line utility to dump passwords and certificates from the user's Keychain, specifically when the initiating process is located in the /tmp/ directory, which is often used by malware for temporary execution.
This rule detects a malicious npm package attempting to read Claude MCP connection settings, which may contain sensitive information like API keys and server details. The theft of MCP configuration could allow attackers to impersonate AI integrations. If this rule triggers, the package should be removed, and any associated API keys should be rotated. Further investigation should involve questioning the user about recent software installations or clicked links, and engaging the security team if the situation remains unclear.
Detects successful outbound network connections to common botnet-associated remote ports (6667, 6697, 8006, 27374, 27375). The rule aggregates these connections by device to identify endpoints communicating with multiple distinct remote IP addresses, a behavior often indicative of botnet participation or command and control activity.
Detects unauthorized access to macOS Keychain for credential extraction
Detects an environment where 'bun' is executing both the primary ('setup.mjs') and secondary ('execution.js' or 'bw_setup.js') payloads within an hour, indicating a potential supply chain attack.
Detects the deletion of .pkg_history or .pkg_logs, an anti-forensic attempt after the dropper completes, associated with the Mastra NPM compromise.
Detects Python transmitting a newly created archive or JSON collection through requests, urllib, aiohttp, or a custom socket. This behavior is associated with the InvisibleFerret malware.
Detects Python searching local vaults and configuration for password managers such as KeePass, 1Password, Bitwarden, or LastPass. This activity is associated with the InvisibleFerret malware.
Detects the creation of a Python launcher file with a '.mod' extension in temporary or user library directories by common script hosts (node, python, wscript, cscript, powershell). This activity is indicative of the InvisibleFerret malware (also known as Void DoKkaebi or BeaverTail) which uses such launchers to import newly downloaded .pyd or .so extensions and supply runtime connection arguments.
Detects the creation or modification of a 'setup.mjs' file within a '.vscode' directory. This script can act as a local payload execution point when developers open infected projects, potentially leading to arbitrary code execution.
Detects outbound network connections to 'seed1.getsession.org', a known Miasma Command and Control domain. This rule specifically looks for network events where the remote URL contains this domain, indicating potential C2 communication.
This rule detects successful network connections from devices to a list of known botnet command and control (C2) IP addresses. This indicates potential compromise and communication with malicious infrastructure.
Detects attempts to exfiltrate environment variables by piping the output of 'env' or 'printenv' commands into 'curl'. This technique can be used by adversaries, such as the Miasma malware, to quickly steal sensitive API keys or other credentials stored in environment variables.
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