Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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The following analytic detects the execution of ngrok.exe on a Windows operating system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. This activity is significant because while ngrok is a legitimate tool for creating secure tunnels, it is increasingly used by adversaries to bypass network defenses and establish reverse proxies. If confirmed malicious, this could allow attackers to exfiltrate data, maintain persistence, or facilitate further attacks by tunneling traffic through the compromised system.
The following analytic detects the execution of a process by `WmiPrvSE.exe`, indicating potential use of WMI (Windows Management Instrumentation) for process creation. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and parent process relationships. This activity is significant as WMI can be used for lateral movement, remote code execution, or persistence by attackers. If confirmed malicious, this could allow an attacker to execute arbitrary commands or scripts, potentially leading to further compromise of the affected system or network.
The following analytic detects the use of Windows Curl.exe to upload a file to a remote destination.
It identifies command-line arguments such as `-T`, `--upload-file`, `-d`, `--data`, and `-F` in process execution logs.
This activity is significant because adversaries may use Curl to exfiltrate data or upload malicious payloads. If confirmed malicious, this could lead to data breaches or further compromise of the system.
Analysts should review parallel processes and network logs to determine if the upload was successful and isolate the endpoint if necessary.
It identifies command-line arguments such as `-T`, `--upload-file`, `-d`, `--data`, and `-F` in process execution logs.
This activity is significant because adversaries may use Curl to exfiltrate data or upload malicious payloads. If confirmed malicious, this could lead to data breaches or further compromise of the system.
Analysts should review parallel processes and network logs to determine if the upload was successful and isolate the endpoint if necessary.
The following analytic detects the use of `dism.exe` to remove Windows Defender. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions that include specific parameters for disabling and removing Windows Defender. This activity is significant because adversaries may disable Defender to evade detection and carry out further malicious actions undetected. If confirmed malicious, this could lead to the attacker gaining persistent access, executing additional payloads, or exfiltrating sensitive data without being intercepted by Windows Defender.
The following analytic detects the execution of common network sniffing tools on Windows systems, including Wireshark, WinPcap, tcpdump, and similar utilities.
This activity is significant because attackers use packet capture tools to intercept and analyze network traffic, enabling credential theft, sensitive data harvesting, and reconnaissance of internal network communications.
While these tools have legitimate administrative uses, their presence in unexpected environments may indicate an adversary conducting man-in-the-middle attacks or exfiltrating sensitive information traversing the network.
If confirmed malicious, this could lead to the exposure of credentials, session tokens, and confidential data, facilitating lateral movement and further compromise of the environment.
This activity is significant because attackers use packet capture tools to intercept and analyze network traffic, enabling credential theft, sensitive data harvesting, and reconnaissance of internal network communications.
While these tools have legitimate administrative uses, their presence in unexpected environments may indicate an adversary conducting man-in-the-middle attacks or exfiltrating sensitive information traversing the network.
If confirmed malicious, this could lead to the exposure of credentials, session tokens, and confidential data, facilitating lateral movement and further compromise of the environment.
The following analytic identifies command-line activity that searches for files related to password manager software, such as "*.kdbx*" and "*credential*". It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs. This activity is significant because attackers often target password manager databases to extract stored credentials, which can be used for further exploitation. If confirmed malicious, this behavior could lead to unauthorized access to sensitive information, enabling attackers to escalate privileges, move laterally, or exfiltrate critical data.
Detects anomalous process execution and loopback network activity associated with the Model Context Protocol (MCP) 'exec_in_session' method. This pattern indicates an adversary potentially abusing the AI coding assistant's MCP server capabilities to execute arbitrary commands as a C2 channel.
The following analytic detects the execution of AdvancedRun.exe, a tool with capabilities similar to remote administration programs like PsExec. It identifies the process by its name or original file name and flags common command-line arguments. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and command-line telemetry. Monitoring this activity is crucial as AdvancedRun can be used for remote code execution and configuration-based automation. If malicious, this could allow attackers to execute arbitrary commands, escalate privileges, or maintain persistence within the environment.
The following analytic detects the usage of wevtutil.exe with parameters for clearing event logs such as Application, Security, Setup, Trace, or System.
It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments.
This activity is significant because clearing event logs can be an attempt to cover tracks after malicious actions, hindering forensic investigations.
If confirmed malicious, this behavior could allow an attacker to erase evidence of their activities, making it difficult to trace their actions and understand the full scope of the compromise.
It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments.
This activity is significant because clearing event logs can be an attempt to cover tracks after malicious actions, hindering forensic investigations.
If confirmed malicious, this behavior could allow an attacker to erase evidence of their activities, making it difficult to trace their actions and understand the full scope of the compromise.
The following analytic detects the usage of wevtutil.exe with the "clear-log" parameter in order to clear the contents of logs.
Clearing the event logs can be an attempt to cover tracks after malicious actions, hindering forensic investigations.
Clearing the event logs can be an attempt to cover tracks after malicious actions, hindering forensic investigations.
The following analytic identifies system processes running from unexpected locations outside of paths such as `C:\Windows\System32\` or `C:\Windows\SysWOW64`. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process paths, names, and hashes. This activity is significant as it may indicate a malicious process attempting to masquerade as a legitimate system process. If confirmed malicious, this behavior could allow an attacker to execute code, escalate privileges, or maintain persistence within the environment, posing a significant security risk.
The following analytic detects the execution of hh.exe (HTML Help) spawning a child process, indicating the use of a Compiled HTML Help (CHM) file to execute Windows script code. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process creation events where hh.exe is the parent process. This activity is significant as it may indicate an attempt to execute malicious scripts via CHM files, a known technique for bypassing security controls. If confirmed malicious, this could lead to unauthorized code execution, potentially compromising the system.
The following analytic detects the execution of `wmic.exe` with the `node` switch, indicating an attempt to spawn a local or remote process. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process creation events and command-line arguments. This activity is significant as it may indicate lateral movement or remote code execution attempts by an attacker. If confirmed malicious, the attacker could gain remote control over the targeted system, execute arbitrary commands, and potentially escalate privileges or persist within the environment.
The following analytic detects the execution of sdbinst.exe with parameters indicative of silently creating a shim database. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, parent processes, and command-line arguments. This activity is significant because shim databases can be used to intercept and manipulate API calls, potentially allowing attackers to bypass security controls or achieve persistence. If confirmed malicious, this could enable unauthorized code execution, privilege escalation, or persistent access to the compromised system.
The following analytic identifies child processes spawned from "mshta.exe". It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific child processes like "powershell.exe" and "cmd.exe". This activity is significant because "mshta.exe" is often exploited by attackers to execute malicious scripts or commands. If confirmed malicious, this behavior could allow an attacker to execute arbitrary code, escalate privileges, or maintain persistence within the environment. Monitoring this activity helps in early detection of potential threats leveraging "mshta.exe" for malicious purposes.
The following analytic detects the use of AppCmd.exe to disable HTTP logging on IIS servers. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution events where AppCmd.exe is used with specific parameters to alter logging settings. This activity is significant because disabling HTTP logging can help adversaries hide their tracks and avoid detection by removing evidence of their actions. If confirmed malicious, this could allow attackers to operate undetected, making it difficult to trace their activities and respond to the intrusion effectively.
This analytic detects attempts to create an "ESX Admins" group using the Windows net.exe or net1.exe commands. This activity may indicate an attempt to exploit the VMware ESXi Active Directory Integration Authentication Bypass vulnerability (CVE-2024-37085). Attackers can use this method to gain unauthorized access to ESXi hosts by recreating the "ESX Admins" group after its deletion from Active Directory.
The following analytic detects changes in the ScManager service security descriptor settings. It leverages data from Endpoint Detection and Response (EDR) agents, specifically searching for any process execution involving the "sc.exe" binary with the "sdset" flag targeting the "scmanager" service. If confirmed malicious, this could allow an attacker to escalate their privileges.
The following analytic detects the execution of the Windows OS tool quser.exe, commonly used to gather information about user sessions on a Remote Desktop Session Host server. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs. Monitoring this activity is crucial as quser.exe is often abused by post-exploitation tools like winpeas, used in ransomware attacks to enumerate user sessions. If confirmed malicious, attackers could leverage this information to further compromise the system, maintain persistence, or escalate privileges.
The following analytic identifies the use of `wmic.exe` to enumerate local groups on an endpoint. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs, including command-line details. Monitoring this activity is significant as it can indicate reconnaissance efforts by an attacker to understand group memberships, which could be a precursor to privilege escalation or lateral movement. If confirmed malicious, this activity could allow an attacker to map out privileged groups, aiding in further exploitation and persistence within the environment.
Detects DNS resolutions to popular threat intelligence, reputation, and sandboxing APIs (e.g., VirusTotal, URLScan, AbuseIPDB) originating from non-browser processes on non-analyst workstations. This behavior may indicate an attacker programmatically querying these services to verify if their infrastructure, payloads, or IP addresses are flagged as malicious, or to conduct reconnaissance.
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