Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects a process performing a high volume of file write operations to UNC paths within a short timeframe. It further filters for processes that lack metadata such as company information, description, or digital signatures, and do not load common system DLLs, which is often indicative of potentially malicious or unpacked code attempting to encrypt or exfiltrate data across a network.
Detects processes that execute and remain dormant for more than 120 seconds before performing a high volume of file operations (greater than 50) or initiating a high volume of network connections (greater than 20). This pattern is consistent with malware or beaconing implants attempting to evade detection during automated sandbox analysis.
This rule detects a process performing a high volume of file write operations to UNC paths within a short timeframe. It further filters for processes that lack metadata such as company information, description, or digital signatures, and do not load common system DLLs, which is often indicative of potentially malicious or unpacked code attempting to encrypt or exfiltrate data across a network.
This rule detects two suspicious behaviors associated with OpenSSH components: the direct modification or replacement of critical OpenSSH binaries (/usr/sbin/sshd, /usr/bin/ssh, /usr/bin/scp), or the use of these processes to write files to suspicious or non-standard locations (such as /tmp/ or unauthorized subdirectories within /var/log/), which may indicate credential harvesting or the presence of a backdoor.
This rule detects potential malicious activity characterized by a high volume of file write operations (at least 20 within a 30-minute window) followed by an attempt to delete those files or the files themselves. The rule monitors Sysmon events, specifically looking for processes that exhibit significant write behavior and then initiate a deletion command via cmd.exe, PowerShell, or the native Windows MoveFileEx self-deletion mechanism.
This rule detects a process performing a high volume of file write operations to UNC paths within a short timeframe. It further filters for processes that lack metadata such as company information, description, or digital signatures, and do not load common system DLLs, which is often indicative of potentially malicious or unpacked code attempting to encrypt or exfiltrate data across a network.
Detects file operations (creation, modification, deletion, renaming) involving common SSH key files (id_rsa, id_ed25519) or files located within .ssh directories, initiated by processes typically associated with AI/LLM tools (chatgpt, perplexity, etc.) or generic process names. This may indicate an attempt to exfiltrate or manipulate authentication credentials by unauthorized applications.
Detects the loading of an unsigned DLL by 'quick_share.exe', 'NearbyShare.exe', or 'nearby_sharing.exe' from suspicious directory paths such as User Temp, AppData, or Downloads folders. This behavior is highly indicative of DLL side-loading attempts where an adversary leverages a legitimate, known process to execute malicious code.
Detects the loading of .NET assemblies (DLL, OCX, EXE) from user-writable directories such as AppData\Local\Temp or AppData\Roaming by processes that are not standard .NET development tools. This behavior is often associated with malware loaders, such as OXLOADER, that perform module stomping or use steganographic techniques to execute malicious code in memory via AppDomain.Load.
This rule detects file access or modification events targeting '.env' files, which often store environment variables and sensitive configuration data (such as API keys and credentials). The detection specifically focuses on file paths associated with CI/CD build agents, runners, or workspace directories (e.g., github, gitlab, jenkins, build, runner), where such credentials are high-value targets for attackers seeking to escalate access or pivot within an environment.
This rule detects file access or modification events targeting '.env' files, which often store environment variables and sensitive configuration data (such as API keys and credentials). The detection specifically focuses on file paths associated with CI/CD build agents, runners, or workspace directories (e.g., github, gitlab, jenkins, build, runner), where such credentials are high-value targets for attackers seeking to escalate access or pivot within an environment.
Detects file access events where the powrprof.dll file is accessed within the Avast Software installation directory. This pattern may be indicative of DLL hijacking or unauthorized file interaction targeting components within the Avast security product structure.
Detects the presence of specific file extensions (.p2k, .3396bw_p2k) often associated with ransomware activity, as well as the creation of 'HowToRestoreFiles.txt' which is a common indicator of a ransom note file.
This rule detects various activities related to the installation, configuration, and execution of OpenSSH on Windows systems. It looks for processes adding the OpenSSH server capability, creating the sshd service, generating SSH keys, and the execution of the sshd.exe process. It also includes a specific hash for a known malicious SSH artifact and firewall rule additions containing 'SSH'.
This rule detects various activities associated with the RustDesk remote access tool, including process execution, file staging (RustCustom.zip or rustdesk.exe by hash), firewall rule creation for RustDesk, and service installation related to RustDesk. Detection is based on process names, file names, SHA256 hashes, firewall rule names, and service names.
This rule detects the loading of a machine learning model (e.g., Pickle, PyTorch, or Hugging Face model files) via Python, immediately followed by the creation of a Windows Executable (PE) or Shared Object (.so) file on disk by the same initiating process. This behavior is indicative of an embedded stage-2 loader within a malicious model file, often seen in backdoored Large Language Models (LLMs). The time correlation between the model loading and the file drop is set to 45 seconds to identify immediate post-load execution.
Detects the execution of 'PerfWatson2.exe' when initiated from the user-writable 'AppData\Local' directory. 'PerfWatson2.exe' is a legitimate Windows process associated with the Windows Error Reporting service; its presence or execution from a user directory is indicative of masquerading or potential malware activity.
Detects execution of node-gyp to compile native Node.js addons, which can be leveraged by attackers to execute arbitrary code or build malicious modules during project installation or development. The rule looks for binding.gyp usage and build commands initiated by npm or node processes.
This rule monitors for suspicious process execution and module loading events, specifically targeting file paths and configurations associated with potential AppDomain Manager injection or masquerading techniques (e.g., PerfWatson2.exe, VMware tools, or Chrome setup configurations). It correlates Sysmon and Security event logs to detect known malicious patterns or abnormal file behaviors.
This rule monitors for suspicious process behaviors and module loads involving 'Mixed Reality.exe' and 'Windows Media Player' components. It detects instances where these files are launched by 'svchost.exe', load suspicious files like 'nvdaHelperRemote.dll', or are executed as a child of 'services.exe'. These behaviors are often associated with masquerading or potential process injection techniques.
Detects suspicious processes accessing, reading, or deleting browser credential stores (like 'Login Data', 'cookies.sqlite'). The rule specifically monitors for patterns where non-browser processes interact with these files, particularly when both file read and deletion actions are observed, which is a technique used by Remcos RAT to wipe existing sessions and force re-authentication for harvesting.
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