Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential information stealing activity, specifically the Atomic macOS Stealer (AMOS) malware, by monitoring unauthorized processes accessing Safari cookies and Apple Notes databases, excluding legitimate applications.
Detects potential activity associated with the AMOS infostealer, where common terminal commands (cp or mv) are used to manipulate or replace legitimate Ledger Live or Trezor Suite cryptocurrency wallet applications located in the /Applications directory on macOS.
Detects unauthorized processes reading, copying, or renaming Kerberos ticket cache files (ccache) located in common temporary directories. This behavior is often associated with credential theft and potential Pass the Ticket attacks where adversaries attempt to extract session credentials to perform lateral movement or privilege escalation.
Detects modification of scripts in extension folders.
Detects Python executing a web-administration exploit with valid credential input and explicit two-factor bypass logic, matching the AI-assisted semantic trust-flaw exploitation described by GTIG.
Detects Python or a shell replacing the installed Chrome build with an older package before installing a wallet extension that requires Manifest V2 capabilities. This activity is associated with the InvisibleFerret malware.
Detects instances where VS Code extension-related processes (such as amazonq-lsp or extensionHost) spawn shell processes (bash/sh) that subsequently initiate network activity via curl or wget. This pattern is indicative of potential exploitation where malicious workspace configuration files (e.g., .amazonq/mcp.json) are used to execute shell commands with unauthorized access to cloud credentials.
Detects the spawning of shells (bash, sh) or utility processes (npx) as child processes of Amazon Q or VS Code extension host components. This activity is indicative of exploitation attempts involving malicious Model Context Protocol (MCP) server configurations within workspace environments, as identified by CVE-2026-12957.
Detects the use of 'hdiutil' to mount disk images with the '-nobrowse' flag, initiated by common command-line or scripting interpreters. The '-nobrowse' flag prevents the mounted volume from appearing on the desktop or in Finder, which is a common technique used by attackers to mount malicious disk images stealthily to facilitate execution of payloads while avoiding user detection.
This rule detects potentially malicious software supply chain activity by monitoring for the execution of 'node-gyp' or 'node-pre-gyp' during the installation of Node.js packages (e.g., via npm or yarn). It specifically flags instances where the process or its parent involves suspicious file names or directory paths often associated with 'Miasma' supply chain campaigns, such as references to 'leo-logger', 'binding.gyp', or 'index.js' inside 'node_modules' directories.
Detects network connection activity on common C2 ports from processes executing outside of standard system directories. The rule filters out known system paths on macOS and identifies processes that establish multiple connections to non-private IP addresses, assigning a risk score based on the volume of connections and the duration of the activity to identify potential command and control (C2) beaconing behavior.
Detects the creation or modification of suspicious macOS Launch Agents or Launch Daemons, specifically looking for patterns associated with the 'macOS.Gaslight' malware (e.g., 'com.apple.system.services.activity') or the creation of Launch Agents in user directories by processes masquerading as browser renderers (indicated by '--type=renderer' in the command line, excluding legitimate browsers). This rule aims to identify persistence mechanisms used by malware.
This rule detects suspicious file creation/modification events in common temporary or library directories, or suspicious process creation/execution events, that contain specific developer-related strings. These strings, such as 'OOMWorker process killed by OOM killer', 'Token expiration handling', 'Refresh token logic seems flaky', 'Build failed on main', and 'SQL Injection vulnerability', could indicate the presence of development tools, debugging activity, or potentially malicious scripts/binaries attempting to mimic legitimate development processes or exfiltrate sensitive information. The rule also looks for a specific SHA256 hash, which might be associated with known malicious or suspicious files.
Detects suspicious process activity involving common macOS command-line tools (osascript, sh, bash, zsh, cp) attempting to access sensitive browser data (Chrome, Edge login data, cookies, web data) or macOS keychain files. This rule specifically excludes activity initiated by the browsers themselves to reduce false positives.
Matches the hardcoded VAPID Public Key string used by the extension to bypass browser sandboxes and wake the service worker, indicative of the SNOWBELT malware's command and control mechanism.
This rule detects a multi-stage attack chain on macOS involving a browser or mail client spawning a shell to download a file (DMG) via curl/wget, followed by the mounting of that disk image, execution of an application bundle from the mounted volume, and a subsequent outbound network connection from that application. This behavior is indicative of a user-initiated malware execution chain.
Detects Python or Node.js processes executing command-line interpreters (e.g., cmd.exe, bash) while simultaneously performing network connections. This behavior is indicative of a post-exploitation activity where an attacker leverages language-specific package paths to execute shell commands and establish command-and-control communication.
This rule detects the use of 'curl' to perform HTTP PUT requests with binary data, a technique often employed by malware like Amos Stealer for data exfiltration. It specifically looks for command-line arguments '-X', 'PUT', and '--data-binary' in 'curl' process executions.
This rule detects the execution of specific Python scripts associated with the 'FortiBleed' campaign. These scripts include 'spray_da.py' (domain admin password spray), 'smb_test.py' (SMB validation/lateral movement), 'spider.py' (Active Directory crawler), and 'ad_full_audit.py' (Active Directory full audit). Detection is based on the Python executable (python.exe, python3, etc.) running with these script names in the command line or as the main file executed.
Detects shell/script execution from .git/hooks/ paths, especially when spawning network-connected or unusual child processes. This activity is indicative of Lazarus Group exploiting Git Hooks for persistence and credential theft within developer environments.
Correlates the malware attempting to permanently disable macOS system-wide Gatekeeper functionality (spctl --master-disable).
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