Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule checks if a given IP address falls within the known IP ranges used by Apple's iCloud Private Relay service. It retrieves a list of IPv4 and IPv6 ranges from a GitHub repository and then uses KQL's `ipv4_is_in_any_range` and `ipv6_is_in_any_range` functions to determine if the provided IP address is part of these ranges. This can be used to identify traffic potentially obfuscated by iCloud Private Relay.
Detects the execution of 'osascript' with command-line arguments indicative of a credential phishing attempt, specifically looking for prompts that display a dialog asking for a password with a hidden answer field. This is associated with the Sapphire Sleet threat actor's macOS intrusion techniques.
This rule detects network connections on port 443 made to common public DNS resolvers (1.1.1.1, 8.8.8.8, 8.8.4.4, 9.9.9.9, 149.112.112.112) by processes other than known web browsers. This behavior is atypical for standard endpoint processes and may indicate the use of DNS-over-HTTPS (DoH) for command and control or data exfiltration to bypass network filtering.
Detects the execution of hidden shell scripts (.sh or .command) located within a mounted disk image (.dmg). This pattern is commonly used by macOS infostealers which masquerade as legitimate applications (such as Notion, Arc, or Raycast) to trick users into executing malicious code after mounting the deceptive installer.
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 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 monitors process command lines and file activity for keywords associated with potential reconnaissance, error logs, or debugging artifacts often used during post-exploitation or system profiling. It flags commands or files containing terms like 'memory dump', 'stack trace', 'SQL injection', or 'Redis failure', which may indicate an attacker analyzing system information or attempting to interact with backend services.
This rule detects the use of the JSON-RPC 'eth_call' method by non-browser processes during network connection events. It specifically looks for network connections where the initiating process is not a common web browser (Chrome, Edge, Firefox) and the network traffic or command line contains the 'eth_call' method. This behavior is indicative of malware or other malicious software attempting to interact with blockchain services, potentially for dynamic command and control or address resolution, as described in the Check Point research.
This rule detects the creation or modification of specific Launch Agent or Launch Daemon plist files on macOS, particularly those masquerading as 'com.apple.accountsd'. It also identifies the creation of a hidden directory '.com.apple.accountsd' within '/Library/Application Support'. This activity is highly suspicious as it indicates an attempt to establish persistence or execute malicious code by mimicking legitimate system services.
Detects DNS lookups and network connections to known AI API endpoints (OpenAI, Anthropic, Google Generative Language) initiated by non-standard processes. This rule excludes common web browsers, productivity applications, and development tools to identify potentially unauthorized or suspicious interaction with AI services from internal processes.
Detects unauthorized access or modification to common CI/CD credential files (.npmrc, .pypirc, .git-credentials, jenkins credentials.xml) and CI/CD configuration files (.github/workflows, .gitlab-ci.yml). The rule monitors both file system activities by non-standard processes and the execution of command-line tools that reference these sensitive files.
Detects DNS lookups and network connections to known AI API endpoints (OpenAI, Anthropic, Google Generative Language) initiated by non-standard processes. This rule excludes common web browsers, productivity applications, and development tools to identify potentially unauthorized or suspicious interaction with AI services from internal processes.
Detects unauthorized or non-standard processes attempting to create, modify, or access sensitive cloud configuration and credential files, such as AWS credentials, Azure CLI token caches, or GCP application default credentials. This behavior is indicative of potential credential theft or unauthorized access to cloud environment tokens.
Detects unauthorized access or modification to common CI/CD credential files (.npmrc, .pypirc, .git-credentials, jenkins credentials.xml) and CI/CD configuration files (.github/workflows, .gitlab-ci.yml). The rule monitors both file system activities by non-standard processes and the execution of command-line tools that reference these sensitive files.
Detects anomalous file modification or deletion events targeting the SSH known_hosts file. This activity can be indicative of VECT ransomware, which zeroes out this file across compromised Linux and ESXi systems to suppress host-key warnings, enabling silent lateral movement via SCP and SSH.
Detects file creation or modification events targeting sensitive cloud credential storage locations, such as AWS credentials files, Azure configurations, and Google Cloud credentials databases. The rule filters out known legitimate CLI tools, flagging potential unauthorized access or exfiltration of cloud credentials by other processes.
Detects unauthorized processes (those not identified as standard web browsers) accessing browser profile directories (Local Storage or IndexedDB) associated with major AI platforms such as OpenAI, ChatGPT, Anthropic, and Copilot. This behavior is indicative of credential theft or session token exfiltration from local browser storage.
Detects file creation or modification events targeting sensitive cloud credential storage locations, such as AWS credentials files, Azure configurations, and Google Cloud credentials databases. The rule filters out known legitimate CLI tools, flagging potential unauthorized access or exfiltration of cloud credentials by other processes.
This rule identifies if a given IP address falls within the known IP ranges used by Apple's iCloud Private Relay service. It leverages an external CSV file containing these IP ranges for both IPv4 and IPv6. This can be used to detect or monitor traffic potentially obfuscated by iCloud Private Relay.
Detects potential command injection attacks against AI agents through
suspicious prompt patterns or system command execution by AI processes.
suspicious prompt patterns or system command execution by AI processes.
Detects curl or wget fetching a secondary payload (like AMOS or ClearFake) directly into the /tmp directory, a volatile location to hide execution artifacts. The rule specifically looks for command-line arguments that use '-o' to specify a destination path within /tmp with common executable or package extensions.
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