Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 network traffic associated with Wazza phishkit anti-bot gates, including beacon communications, TLS SNI patterns, fingerprint iframe URIs, and challenge-platform requests.
Detects PowerShell execution performing port checks across multiple internal hosts using Test-NetConnection in a looping construct with output redirected to a log file, indicative of post-compromise reconnaissance (such as LONEPAGE scanning).
The following analytic detects the usage of the SharpHound binary by identifying its original filename, `SharpHound.exe`, and the process name. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process metadata and command-line executions. SharpHound is a tool used for Active Directory enumeration, often by attackers during the reconnaissance phase. If confirmed malicious, this activity could allow an attacker to map out the network, identify high-value targets, and plan further attacks, potentially leading to privilege escalation and lateral movement within the environment.
The following analytic detects the execution of `powershell.exe` running the `Get-ADDefaultDomainPasswordPolicy` cmdlet, which is used to retrieve the password policy in a Windows domain.
This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions.
Monitoring this activity is crucial as it can indicate attempts by adversaries to gather information about domain policies for situational awareness and Active Directory discovery.
If confirmed malicious, this activity could lead to further reconnaissance and potential exploitation of domain security settings.
This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions.
Monitoring this activity is crucial as it can indicate attempts by adversaries to gather information about domain policies for situational awareness and Active Directory discovery.
If confirmed malicious, this activity could lead to further reconnaissance and potential exploitation of domain security settings.
The following analytic detects the execution of `powershell.exe` with command-line arguments used to enumerate domain users via the `Get-DomainUser` command. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions mapped to the `Processes` node of the `Endpoint` data model. This activity is significant as it indicates potential reconnaissance efforts by adversaries or Red Teams using PowerView for Active Directory discovery. If confirmed malicious, this could allow attackers to gain situational awareness and identify valuable targets within the domain, potentially leading to further exploitation.
The following analytic detects the execution of `powershell.exe` with the `Get-LocalUser` commandlet, which is used to query local user accounts. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. Monitoring this activity is significant because adversaries and Red Teams may use it to enumerate local users for situational awareness and Active Directory discovery. If confirmed malicious, this activity could allow attackers to identify potential targets for further exploitation or privilege escalation within the environment.
The following analytic detects suspicious file and directory discovery activities, which may indicate an attacker's effort to locate sensitive documents and files on a compromised system. This behavior often precedes data exfiltration, as adversaries seek to identify valuable or confidential information for theft. By identifying unusual or unauthorized attempts to browse or enumerate files and directories, this analytic helps security teams detect potential reconnaissance or preparatory actions by an attacker, enabling timely intervention to prevent data breaches or unauthorized access.
The following analytic detects the suspicious use of the whoami command, which may indicate an attacker trying to gather information about the current user account on a compromised system. The whoami command is commonly used to verify user privileges and identity, especially during initial stages of an attack to assess the level of access. By monitoring for unusual or unauthorized executions of whoami, this analytic helps in identifying potential reconnaissance activities, enabling security teams to take action before the attacker escalates privileges or conducts further malicious operations.
The following analytic identifies the use of the 'kmod' process to list kernel modules on a Linux system. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. While listing kernel modules is not inherently malicious, it can be a precursor to loading unauthorized modules using 'insmod'. If confirmed malicious, this activity could allow an attacker to load kernel modules, potentially leading to privilege escalation, persistence, or other malicious actions within the system.
The following analytic identifies potential enumeration of local network configuration on Linux systems.
It detects this activity by monitoring processes such as "arp," "ifconfig," "ip," "netstat," "firewall-cmd," "ufw," "iptables," "ss," and "route" within a 30-minute window.
This behavior is significant as it often indicates reconnaissance efforts by adversaries to gather network information for subsequent attacks.
If confirmed malicious, this activity could enable attackers to map the network, identify vulnerabilities, and plan further exploitation or lateral movement within the environment.
It detects this activity by monitoring processes such as "arp," "ifconfig," "ip," "netstat," "firewall-cmd," "ufw," "iptables," "ss," and "route" within a 30-minute window.
This behavior is significant as it often indicates reconnaissance efforts by adversaries to gather network information for subsequent attacks.
If confirmed malicious, this activity could enable attackers to map the network, identify vulnerabilities, and plan further exploitation or lateral movement within the environment.
Identifies execution of network share enumeration commands (smbutil, showmount) that can be leveraged by adversaries to discover accessible SMB and NFS resources, supporting internal reconnaissance and potential lateral movement.
The following analytic detects the use of the `[Adsisearcher]` type accelerator in PowerShell scripts to query Active Directory for domain computers. It leverages PowerShell Script Block Logging (EventCode=4104) to identify specific script blocks containing `adsisearcher` and `objectcategory=computer` with methods like `findAll()` or `findOne()`. This activity is significant as it may indicate an attempt by adversaries or Red Teams to perform Active Directory discovery and gain situational awareness. If confirmed malicious, this could lead to further reconnaissance and potential lateral movement within the network.
The following analytic identifies the execution of `net.exe` with command-line arguments used to query global, local and domain groups. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. This activity is significant as it indicates potential reconnaissance efforts by adversaries to enumerate local or domain groups, which is a common step in Active Directory or privileged accounts discovery. If confirmed malicious, this behavior could allow attackers to gain insights into the domain structure, aiding in further attacks such as privilege escalation or lateral movement.
The following analytic detects the enumeration of Windows services using the net start command, which is a built-in utility that lists all running services on a system. Adversaries, system administrators, or automated tools may use this command to gain situational awareness of what services are active, identify potential security software, or discover opportunities for privilege escalation and lateral movement. The execution of net start is often associated with reconnaissance activity during the early stages of an intrusion, as attackers attempt to map out the system’s defense mechanisms and operational services. By monitoring process execution for instances of cmd.exe /c net start or similar command-line usage, defenders can detect potentially suspicious activity. Correlating this behavior with other reconnaissance commands, such as tasklist or sc query, strengthens detection fidelity. While net start is not inherently malicious, unusual or repeated use in non-administrative contexts should be flagged for further investigation.
The following analytic identifies network share discovery and collection activities performed on Windows systems using the Net command. Attackers often use network share discovery to identify accessible shared resources within a network, which can be a precursor to privilege escalation or data exfiltration. By monitoring Windows Event Logs for the usage of the Net command to list and interact with network shares, this detection helps identify potential reconnaissance and collection activities.
The following analytic detects the use of the `[Adsisearcher]` type accelerator in PowerShell to query Active Directory for root domain linked policies. It leverages PowerShell Script Block Logging (EventCode=4104) to identify this activity. This behavior is significant as it may indicate an attempt by adversaries or Red Teams to gain situational awareness and perform Active Directory Discovery. If confirmed malicious, this activity could allow attackers to map out domain policies, potentially aiding in further exploitation or lateral movement within the network.
The following analytic detects the execution of the Windows built-in tool netsh.exe to display the state, configuration, and profile of the host firewall. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions and process metadata. Monitoring this activity is crucial as netsh.exe can be used by adversaries to bypass firewall rules or discover firewall settings. If confirmed malicious, this activity could allow attackers to manipulate firewall configurations, potentially leading to unauthorized network access or data exfiltration.
The following analytic identifies the use of the w32tm.exe utility with the /stripchart function, which is indicative of DCRat malware delaying its payload execution. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line arguments used by w32tm.exe. This activity is significant as it may indicate an attempt to evade detection by delaying malicious actions such as C2 communication and beaconing. If confirmed malicious, this behavior could allow an attacker to maintain persistence and execute further malicious activities undetected.
The following analytic detects the execution of Windows Management Instrumentation Command-line (WMIC) commands used for computer system discovery on a Windows system. Specifically, it monitors for commands such as “wmic computersystem” that retrieve detailed information about the computer’s model, manufacturer, name, domain, and other system attributes. While these commands are commonly used by administrators for inventory and troubleshooting, they may also be exploited by adversaries to gain insight into the target environment during the reconnaissance phase of an attack. Identifying and alerting on WMIC computer system queries helps security teams recognize unauthorized information gathering and take steps to mitigate potential threats.
Detects HTTP traffic associated with the Wazza phishing kit anti-bot mechanism, including token minting requests, signed token responses, and validation checks.
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