Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of 'vsdbg.exe' or 'vsdbg.dll' from locations outside of the legitimate Microsoft Visual Studio installation directories. This behavior is indicative of potentially malicious usage of the Visual Studio debugger components for process injection or evasion.
Detects the loading or file presence of the malicious kernel driver 'Alinubx.sys' (formerly 'CcProtect.sys'), which is utilized by attackers for Bring Your Own Vulnerable Driver (BYOVD) attacks to terminate security software processes from kernel mode.
This rule detects the presence and execution of known suspicious files (hashes provided) or specific malicious artifacts, such as 'hmn_hook.dll' being loaded, or the execution of binaries named 'auto.exe' and '78324.exe' associated with specific command-line arguments. It monitors file events, image loads, and process creation to identify potential malware activity.
This rule detects the addition or modification of Windows Firewall rules by applications residing in non-standard or suspicious directories. It monitors Security Events 2004, 2071, and 2097, filtering out known legitimate system paths, common temporary directories, and updates from trusted Microsoft processes such as Windows Defender, svchost.exe, and dllhost.exe. By excluding standard operating system folders and common software installation paths, the rule highlights potentially malicious attempts to establish persistence or facilitate unauthorized network communication by bypassing standard firewall management channels.
Detects the use of PowerShell's Start-Sleep cmdlet with a duration of 3 minutes or longer within process command lines. This technique is commonly used by malware, such as ClickFix-style droppers, to bypass sandbox time-based analysis by delaying execution until the sandbox timeout period has elapsed.
Detects the execution of Windows Script Host (WScript.exe or CScript.exe) that creates a file or folder starting with 'Libs_' within the 'C:\Users\Public\' directory. This activity is often associated with attackers staging payloads, configuration files, or tools in publicly writable folders to evade detection.
Detects suspicious file activity where a script or process creates a staging folder within 'C:\Users\Public\' and subsequently writes potential decoy PDF files or compressed archive payloads to that same directory. This behavior is indicative of a dropper or secondary stage malware delivery mechanism utilizing world-writable directories for staging.
Detects instances where the Notepad++ executable is launched from a location within the C:\Users\Public\ directory, specifically when the parent process is a Windows scripting engine (wscript.exe or cscript.exe). This pattern is often indicative of an adversary executing a malicious payload staged in a common public directory using script-based wrappers to bypass execution policy or maintain stealth.
This rule detects instances where Windows script hosts (wscript.exe or cscript.exe) create directories with suspicious naming conventions (starting with 'Libs_' or containing 'Temp Documents') within the 'C:\Users\Public\' directory. This activity is often associated with the staging of malicious payloads or collected data prior to exfiltration or execution.
Detects instances where the Windows Script Host (wscript.exe) spawns a process to open a PDF file located within the Public user's 'Temp Documents' directory. This behavior is indicative of a potential malware staging or execution attempt where an adversary attempts to open a malicious document from a publicly accessible folder to bypass user suspicion or execute malicious content.
Detects VBScript droppers that utilize excessive 'WScript.Sleep' delays to bypass sandbox analysis, often combined with error suppression and downloader APIs to execute malicious payloads.
Detects network connections, process command line arguments, and DNS queries associated with identified Galago or Panzer ransomware C2, leak site, or contact infrastructure (Tox IDs/Tor .onion addresses).
Detects network connections, process command line arguments, and DNS queries associated with identified Galago or Panzer ransomware C2, leak site, or contact infrastructure (Tox IDs/Tor .onion addresses).
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
This rule identifies potential malicious activity by detecting the presence of known malicious file hashes (SHA256 and MD5) on endpoints and monitoring for DNS queries or network connections to a known malicious staging domain (yapw.life). The detection correlates file execution, file activity, and network communication to identify stages of an attack such as malware installation or C2 communication.
Detects rapid, machine-speed, sequential attack-path adaptation by suspected AI agent binaries. The rule monitors for a correlation of four stages occurring within a tight 20-minute window: 1) Failed service connections across three or more distinct protocols (SMB, SSH, HTTP, RDP, WinRM), 2) Credential access attempts (Logon events or execution of known credential-dumping tools), and 3) A lateral movement pivot to a new, previously un-targeted internal destination. The rule specifically keys on the InitiatingProcessId and InitiatingProcessCreationTime to ensure the sequence is attributed to a single process instance, distinguishing it from human manual penetration testing activity. Covers T1190, T1210, T1078
Detects rapid, machine-speed, sequential attack-path adaptation by suspected AI agent binaries. The rule monitors for a correlation of four stages occurring within a tight 20-minute window: 1) Failed service connections across three or more distinct protocols (SMB, SSH, HTTP, RDP, WinRM), 2) Credential access attempts (Logon events or execution of known credential-dumping tools), and 3) A lateral movement pivot to a new, previously un-targeted internal destination. The rule specifically keys on the InitiatingProcessId and InitiatingProcessCreationTime to ensure the sequence is attributed to a single process instance, distinguishing it from human manual penetration testing activity. Covers T1190, T1210, T1078
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