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 `nltest.exe` with command-line arguments `/dclist:` or `/dsgetdc:` to discover domain controllers. It leverages Endpoint Detection and Response (EDR) data, focusing on process names and command-line arguments. This activity is significant because both Red Teams and adversaries use `nltest.exe` for situational awareness and Active Directory discovery. If confirmed malicious, this behavior could allow attackers to map out domain controllers, facilitating further attacks such as privilege escalation or lateral movement within the network.
This analytic detects the execution of rundll32.exe without any command-line arguments, immediately followed by a network connection. This behavior is suspicious because rundll32.exe typically requires arguments to perform legitimate functions. Its use without arguments, especially when combined with network activity, is often indicative of malicious activity, such as the execution of Cobalt Strike beacons or other malware attempting to establish unauthorized network communications for data exfiltration or further system compromise. The detection relies on correlating endpoint process telemetry with network traffic data.
This analytic detects a Windows application establishing an SMTP connection from a non-common installation path. It leverages Sysmon EventCode 3 to identify processes not typically associated with email clients (e.g., Thunderbird, Outlook) making SMTP connections. This activity is significant as adversaries, including malware like AgentTesla, use such connections for Command and Control (C2) communication to exfiltrate stolen data. If confirmed malicious, this behavior could lead to unauthorized data exfiltration, including sensitive information like desktop screenshots, browser data, and system details, compromising the affected host.
This analytic detects IPv6 network infrastructure threats by identifying suspicious activities such as IP and MAC address theft or packet drops. It leverages logs from Cisco network devices configured with First Hop Security measures like RA Guard and DHCP Guard. This activity is significant as it can indicate attempts to compromise network integrity and security. If confirmed malicious, attackers could manipulate network traffic, leading to potential data interception, unauthorized access, or network disruption.
The following analytic identifies suspicious Office documents that connect to non-Microsoft Office domains. It leverages Sysmon EventCode 22 to detect processes like winword.exe or excel.exe making DNS queries to domains outside of *.office.com or *.office.net. This activity is significant as it may indicate a spearphishing attempt using malicious documents to download or connect to harmful content. If confirmed malicious, this could lead to unauthorized data access, malware infection, or further network compromise.
The following analytic detects the creation of AWS Network Access Control Lists (ACLs) with all ports open to a specified CIDR. It leverages AWS CloudTrail events, specifically monitoring for `CreateNetworkAclEntry` or `ReplaceNetworkAclEntry` actions with rules allowing all traffic. This activity is significant because it can expose the network to unauthorized access, increasing the risk of data breaches and other malicious activities. If confirmed malicious, an attacker could exploit this misconfiguration to gain unrestricted access to the network, potentially leading to data exfiltration, service disruption, or further compromise of the AWS environment.
The following analytic detects the creation or update of a Kubernetes pod with host network attachment. It leverages Kubernetes Audit logs to identify pods configured with host network settings. This activity is significant for a SOC as it could allow an attacker to monitor all network traffic on the node, potentially capturing sensitive information and escalating privileges. If confirmed malicious, this could lead to unauthorized access, data breaches, and service disruptions, severely impacting the security and integrity of the Kubernetes environment.
The following analytic detects the execution of nslookup.exe to query domain information using LDAP. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. This activity is significant as nslookup.exe can be abused by malware like Qakbot to gather critical domain details, such as SRV records and server names. If confirmed malicious, this behavior could allow attackers to map the network, identify key servers, and plan further attacks, potentially leading to data exfiltration or lateral movement within the network.
The following analytic identifies web requests to domains that closely resemble your monitored brand's domain, indicating potential brand abuse. It leverages data from web traffic sources, such as web proxies or network traffic analysis tools, and cross-references these with known domain permutations generated by the "ESCU - DNSTwist Domain Names" search. This activity is significant as it can indicate phishing attempts or other malicious activities targeting your brand. If confirmed malicious, attackers could deceive users, steal credentials, or distribute malware, leading to significant reputational and financial damage.
The 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.
The analytic identifies the loading of the malicious SolarWinds.Orion.Core.BusinessLayer.dll by SolarWinds.BusinessLayerHost.exe and subsequent DNS queries to avsvmcloud.com. It uses Sysmon EventID 7 for DLL loading and Event ID 22 for DNS queries, correlating these events within a 12-14 day period. This activity is significant as it indicates potential Sunburst malware infection, a known supply chain attack. If confirmed malicious, this could lead to unauthorized network access, data exfiltration, and further compromise of the affected systems.
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 analytic detects attempts to exploit the SIGRed vulnerability (CVE-2020-1350) in Windows DNS servers. It leverages Splunk Stream DNS and TCP data to identify DNS SIG and KEY records, as well as TCP payloads exceeding 65KB. This activity is significant because SIGRed is a critical wormable vulnerability that allows remote code execution. If confirmed malicious, an attacker could gain unauthorized access, execute arbitrary code, and potentially disrupt services, leading to severe data breaches and infrastructure compromise. Immediate investigation and remediation are crucial to mitigate these risks.
The following analytic identifies DNS requests with unusually large query lengths for the record type being requested. It leverages the Network_Resolution data model and applies a machine learning model to detect outliers in DNS query lengths. This activity is significant because unusually large DNS queries can indicate data exfiltration or command-and-control communication attempts. If confirmed malicious, this activity could allow attackers to exfiltrate sensitive data or maintain persistent communication channels with compromised systems.
This analytic identifies potential exploitation attempts on a known vulnerability in Atlassian Confluence, specifically targeting the /setup/*.action* URL pattern. It leverages web logs within the Splunk 'Web' Data Model, filtering for successful accesses (HTTP status 200) to these endpoints. This activity is significant as it suggests attackers might be exploiting a privilege escalation flaw in Confluence. If confirmed malicious, it could result in unauthorized access or account creation with escalated privileges, leading to potential data breaches or further exploitation within the environment.
The analytic detects the use of the Nishang Invoke-PowerShellTCPOneLine utility, which initiates a callback to a remote Command and Control (C2) server. It leverages Endpoint Detection and Response (EDR) data, focusing on PowerShell processes that include specific .NET classes like Net.Sockets.TCPClient and System.Text.ASCIIEncoding. This activity is significant as it indicates potential remote control or data exfiltration attempts by an attacker. If confirmed malicious, this could lead to unauthorized remote access, data theft, or further compromise of the affected system.
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.
This analytic identifies DNS queries from internal hosts to dynamic domain providers. It leverages DNS query logs from the `Network_Resolution` data model and cross-references them with a lookup file containing known dynamic DNS providers. This activity is significant because attackers often use dynamic DNS services to host malicious payloads or command-and-control servers, making it crucial for security teams to monitor. If confirmed malicious, this activity could allow attackers to bypass firewall blocks, evade detection, and maintain persistent access to the network.
This analytic identifies DNS queries with unusually large lengths by computing the standard deviation of query lengths and filtering those exceeding twice the standard deviation. It leverages DNS query data from the Network_Resolution data model, focusing on the length of the domain names being resolved. This activity is significant as unusually long DNS queries can indicate data exfiltration or command-and-control communication attempts. If confirmed malicious, this activity could allow attackers to stealthily transfer data or maintain persistent communication channels within the network.
The analytic identifies the execution of `powershell.exe` with the `Get-NetTcpConnection` command, which lists current TCP connections on a system. This activity may indicate an adversary or Red Team performing network reconnaissance or situational awareness, potentially aiding in lateral movement or further exploitation within the network.
The following analytic identifies the execution of `net.exe` with command-line arguments used to list or display information about computer connections. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity can be significant as it indicates potential network reconnaissance by adversaries or Red Teams, aiming to gather situational awareness and Active Directory information. If confirmed malicious, this behavior could allow attackers to map the network, identify critical assets, and plan further attacks, potentially leading to data exfiltration or lateral movement.
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