Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
503 detections
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Detects potential SafePay ransomware activity by correlating mass file encryption (.safepay extension) with the creation of potential ransom notes and subsequent self-deletion of the encrypting process.
Detects potential SafePay ransomware activity by correlating mass file encryption (.safepay extension) with the creation of potential ransom notes and subsequent self-deletion of the encrypting process.
Detects the execution of rm commands using force flags to delete multiple critical appliance, system, and web server log files simultaneously on Linux hosts.
Detects the execution of rm commands using force flags to delete multiple critical appliance, system, and web server log files simultaneously on Linux hosts.
Detects the execution of rm commands using force flags to delete multiple critical appliance, system, and web server log files simultaneously on Linux hosts.
Detects the execution of rm commands using force flags to delete multiple critical appliance, system, and web server log files simultaneously on Linux hosts.
Detects the execution of rm commands using force flags to delete multiple critical appliance, system, and web server log files simultaneously on Linux hosts.
Detects the Shai-Hulud supply chain attack dead-man's switch: a gh-token-monitor persistence component followed by a recursive forced deletion of the user home directory, or the presence of the specific kill-switch string in a command line.
Detects two distinct suspicious patterns: first, the deletion of executable files residing in common user-writable temporary directories (e.g., Temp, Downloads, AppData) using command-line tools like 'del' or 'erase', which is often indicative of anti-forensic activity after malware execution. Second, it monitors for network traffic involving HTTP POST requests or specific SOAP headers related to 'tempuri.org', which are commonly associated with default .NET WCF service scaffolding and may be used by adversaries for C2 communication or exfiltration.
This rule detects potential anti-forensic activity on Citrix ADC/NetScaler devices by monitoring for two primary indicators of log tampering: an unexpected drop in syslog volume to zero following a period of activity, or the execution of explicit commands intended to clear audit logs and configuration files.
Detects the specific command-line sequence used by SectopRAT for self-deletion. The malware uses 'choice' to create a delay followed by a 'del' command to remove its own executable, a technique for deleting files after the process has terminated.
Detects a burst of file delete or overwrite operations initiated by a configured AI agent service identity. This behavior, if deviating from established baselines, may indicate a compromised agent performing malicious destructive activities such as mass data deletion or ransomware-style file destruction.
Detects unauthorized file deletion activity performed directly by a Node.js process acting as a ChainScript RAT. The RAT uses a bundled node.exe process, operating within specific masquerading directories in the user profile, to execute file system operations such as recursive deletion without spawning child processes.
Detects the execution of the DEL command via cmd.exe spawned by sqlservr.exe, specifically targeting batch scripts, executables, or text files located within AppData or ServiceProfiles paths. This behavior is indicative of post-exploitation activity where an attacker removes staging artifacts used during lateral movement or persistence phases to hide their tracks after using xp_cmdshell.
Detects two distinct suspicious patterns: first, the deletion of executable files residing in common user-writable temporary directories (e.g., Temp, Downloads, AppData) using command-line tools like 'del' or 'erase', which is often indicative of anti-forensic activity after malware execution. Second, it monitors for network traffic involving HTTP POST requests or specific SOAP headers related to 'tempuri.org', which are commonly associated with default .NET WCF service scaffolding and may be used by adversaries for C2 communication or exfiltration.
Detects two distinct suspicious patterns: first, the deletion of executable files residing in common user-writable temporary directories (e.g., Temp, Downloads, AppData) using command-line tools like 'del' or 'erase', which is often indicative of anti-forensic activity after malware execution. Second, it monitors for network traffic involving HTTP POST requests or specific SOAP headers related to 'tempuri.org', which are commonly associated with default .NET WCF service scaffolding and may be used by adversaries for C2 communication or exfiltration.
Detects the deletion, truncation, or modification of critical PaperCut server logs and application files (server.log, pcxboot_l.txt, .bin files). This activity is associated with attempts to conceal exploitation of PaperCut vulnerabilities (e.g., CVE-2026-82078/81578) by clearing logs or tampering with binaries, typically executed by the PaperCut application processes themselves (pc-app.exe or Java runtime).
Detects anomalous database activity on Magento e-commerce platforms where a SELECT operation against sensitive payment-related tables is followed by a DELETE operation on the same table within the same host context. This sequence is indicative of an attacker exfiltrating credit card data and subsequently attempting to remove forensic evidence of the theft.
Detects the execution of the sckit Go implant, linked to the MemTensor supply chain compromise, during its host-profiling stage. The rule monitors for the 'sckit' binary being executed with 'stage0' and '--config64' command-line arguments, or being spawned by legitimate runtime interpreters like Node.js or Python, indicating an attempt to profile host information (timezone, language, privileges) and subsequent self-deletion.
Detects suspicious execution patterns characteristic of post-exploitation activity, such as invoking 'go run' or 'node' from non-standard directories like AppData or Temp, as well as the use of command-line routines to delete files after execution (often associated with self-deleting secondary payloads or persistence cleanup).
Detects instances where a process attempts to delete its own executable file image shortly after being launched. This behavior is often associated with malware attempting to minimize its forensic footprint, such as self-deleting installers or RAT (Remote Access Trojan) components that move to a different location or execute from memory.
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