Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of system utilities commonly used on macOS to discover network connections and logged-in users. These utilities include 'who', 'w', 'last', 'lsof', and 'netstat'. Adversaries may use these commands during the discovery phase to understand the network environment and identify potential targets or communication paths.
This rule detects the use of 'dd' and 'truncate' utilities to add junk data to a file, a technique known as binary padding. Adversaries may use this method to alter the on-disk representation of malware, potentially bypassing security tools that have file size limitations or rely on hash-based detection.
This rule detects the execution of AppleScript or JavaScript for Automation (JXA) scripts on macOS systems. It specifically looks for the 'osascript' utility being used with command-line arguments that indicate direct script execution ('-e') or the execution of script files with '.scpt' (AppleScript) or '.js' (JavaScript/JXA) extensions. This activity can be indicative of an adversary using scripting interpreters for execution.
Detects the execution of the 'jamf' binary with specific commands that could be used by attackers for privilege escalation, bypassing security controls, or modifying system configurations. This includes creating user accounts, managing the JAMF framework, removing MDM profiles, resetting passwords, and setting computer names.
This rule detects the execution of system commands commonly used to shut down, reboot, or halt a macOS system. Adversaries may use these commands to disrupt system availability or aid in the destruction of systems.
This rule detects the execution of the 'split' command, which is commonly used to break large files into smaller, more manageable pieces. Adversaries may use this technique to circumvent data transfer size limits during exfiltration or to prepare data for transfer through channels with size restrictions. The detection focuses on the command line execution of the 'split' utility.
This rule detects various suspicious exceptions within Django web applications. These exceptions, such as 'SuspiciousOperation' and its subclasses (e.g., 'DisallowedHost', 'InvalidSessionKey', 'RequestDataTooBig'), as well as 'PermissionDenied', often indicate attempts to exploit vulnerabilities, bypass security controls, or engage in other malicious activities against the web application. Monitoring these exceptions can help identify potential attacks like web parameter tampering, session hijacking attempts, or unauthorized access attempts.
Detects suspicious child processes spawned from web browsers on macOS. This activity often indicates a potential web browser exploitation attempt, where an attacker leverages a browser vulnerability to execute arbitrary commands or scripts on the system. The rule specifically looks for common scripting and command-line interpreters being launched as child processes of various browsers, while filtering out known legitimate browser-related activities like updates or recovery scripts.
Detects the usage of the `base64` utility on macOS to decode arbitrary base64-encoded text. This activity can be indicative of an adversary deobfuscating malicious content, such as scripts or payloads, that were previously encoded to evade detection.
This rule identifies execution traces indicative of the XCSSET macOS malware. XCSSET is known to spread via Xcode projects and maliciously modify applications. The rule looks for specific command-line patterns involving 'curl' to suspicious URLs, 'osacompile' and 'plutil' interacting with user and group containers, and 'zip' archiving data from user and group containers. These activities suggest potential command and control communication, persistence mechanisms, and data staging/exfiltration by the malware.
Detects possible malicious execution of JavaScript for Automation (JXA) in-memory via the `osascript` utility on macOS. This rule specifically looks for command-line executions of `osascript` that include the `-e` flag (for executing a script string), the `eval` function, `NSData.dataWithContentsOfURL` (indicating potential remote content loading), and either explicitly specifies 'JavaScript' as the language or includes '.js' in the command line.
This rule detects common SQL exception types in Python applications as defined by PEP 249. These exceptions (DataError, IntegrityError, ProgrammingError, OperationalError) indicate issues during database operations, which could range from malformed queries to database connectivity problems or constraint violations. While often benign, repeated or unusual occurrences of these errors could signal application vulnerabilities being exploited (e.g., SQL injection attempts leading to syntax errors) or other malicious database interactions.
Detects the creation of a new local user account on macOS systems using either the 'dscl' or 'sysadminctl' commands. Such accounts may be used for persistence without requiring persistent remote access tools.
This rule detects the usage of common macOS command-line utilities for file and directory discovery. Specifically, it looks for executions of '/usr/bin/file' with a very long command line (potentially indicating wildcard usage), '/bin/ls' with the recursive flag '-R', and direct executions of '/usr/bin/find' and '/usr/bin/mdfind'. It also includes a generic detection for '/tree' which might be a custom or less common utility for directory listing.
Detects process execution related errors in NodeJS. If the exceptions are caused due to user input then they may suggest an RCE vulnerability.
Detects potential local file read vulnerability in JVM based apps.
If the exceptions are caused due to user input and contain path traversal payloads then it's a red flag.
If the exceptions are caused due to user input and contain path traversal payloads then it's a red flag.
Detects process execution related exceptions in JVM based apps, often relates to RCE
Detects exceptions in velocity template renderer, this most likely happens due to dynamic rendering of user input and may lead to RCE.
Detects additions to the Emond Launch Daemon that adversaries may use to gain persistence and elevate privileges.
Detects the usage of tooling to sniff network traffic.
An adversary may place a network interface into promiscuous mode to passively access data in transit over the network, or use span ports to capture a larger amount of data.
An adversary may place a network interface into promiscuous mode to passively access data in transit over the network, or use span ports to capture a larger amount of data.
Detection use of the command "split" to split files into parts and possible transfer.
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