Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,006 detections
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The following analytic detects access attempts to privileged Active Directory objects, such as Domain Admins or Enterprise Admins. It leverages Windows Security Event Code 4662 to identify when these sensitive objects are accessed. This activity is significant because such objects should rarely be accessed by normal users or processes, and unauthorized access attempts may indicate attacker enumeration or lateral movement within the domain. If confirmed malicious, this activity could allow attackers to escalate privileges, persist in the environment, or gain control over critical domain resources.
The following analytic detects the use of Impacket's `wmiexec.py` tool for lateral movement by identifying specific command-line parameters. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on processes spawned by `wmiprvse.exe` with command-line patterns indicative of Impacket usage. This activity is significant as Impacket tools are commonly used by adversaries for remote code execution and lateral movement within a network. If confirmed malicious, this could allow attackers to execute arbitrary commands on remote systems, potentially leading to further compromise and data exfiltration.
This rule detects when an authorization token, initially observed in Google Kubernetes Engine (GKE) activity logs, is subsequently used within a command line on an endpoint system. This behavior suggests that a GKE pod's credential may have been exfiltrated and is being reused on a different system, potentially indicating unauthorized access or credential theft.
The following analytic detects changes to computer accounts using an anonymous logon. It leverages Windows Security Event Codes 4742 (Computer Change) and 4624 (Successful Logon) with the TargetUserName set to "ANONYMOUS LOGON" and LogonType 3. This activity is significant because anonymous logons should not typically be modifying computer accounts, indicating potential unauthorized access or misconfiguration. If confirmed malicious, this could allow an attacker to alter computer accounts, potentially leading to privilege escalation or persistent access within the network.
The analytic detects the use of NetExec (formerly CrackMapExec), a toolset for post-exploitation enumeration and attack within Active Directory environments, by identifying specific command-line arguments. It leverages Endpoint Detection and Response (EDR) data to detect actions like ticket manipulation, Kerberoasting, and password spraying. This activity is significant as NetExec is used by adversaries to exploit Kerberos for privilege escalation and lateral movement, potentially leading to unauthorized access, persistence, and compromise of sensitive information.
The analytic detects cloud provisioning activities originating from previously unseen regions. It leverages cloud infrastructure logs to identify events where resources are started or created, and cross-references these with a baseline of known regions. This activity is significant as it may indicate unauthorized access or misuse of cloud resources from unfamiliar locations. If confirmed malicious, this could lead to unauthorized resource creation, potential data exfiltration, or further compromise of cloud infrastructure.
The analytic detects spikes in Server Message Block (SMB) traffic connections, which are used for sharing files and resources between computers. It leverages network traffic logs to monitor connections on ports 139 and 445, and SMB application usage. By calculating the average and standard deviation of SMB connections over the past 70 minutes, it identifies sources exceeding two standard deviations from the average. This activity is significant as it may indicate potential SMB-based attacks, such as ransomware or data theft. If confirmed malicious, attackers could exfiltrate data or spread malware within the network.
This analytic identifies the use of `certutil.exe` with arguments indicating the manipulation or extraction of certificates. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. This activity is significant because extracting certificates can allow attackers to sign new authentication tokens, particularly in federated environments like Windows ADFS. If confirmed malicious, this could enable attackers to forge authentication tokens, potentially leading to unauthorized access and privilege escalation within the network.
This analytic detects the execution of `mofcomp.exe` loading a MOF file, particularly when initiated by `cmd.exe` or `powershell.exe`, or when `mofcomp.exe` is executed from unusual paths such as user profile directories (`*\AppData\Local\*` or `*\Users\Public\*`). This activity is significant because adversaries often use WMI for persistence or lateral movement. Successful exploitation could lead to arbitrary code execution, persistence, or privilege escalation within the environment.
The following analytic identifies the execution of `PsExec.exe` with the `accepteula` flag in the command line. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs and command-line arguments. This activity is significant because PsExec is commonly used by threat actors to execute code on remote systems, and the `accepteula` flag indicates first-time usage, which could signify initial compromise. If confirmed malicious, this activity could allow attackers to gain remote code execution capabilities, potentially leading to further system compromise and lateral movement within the network.
This rule detects suspicious PowerShell commands that modify firewall rules to allow inbound traffic to a specific local port. This activity is significant because it may indicate an attacker attempting to establish remote access by modifying firewall rules, potentially leading to unauthorized access and further exploitation.
This analytic identifies `mmc.exe` spawning a Living Off The Land Binaries and Scripts (LOLBAS) execution process. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process creation events where `mmc.exe` is the parent process. This activity is significant because adversaries can abuse the DCOM protocol and MMC20 COM object to execute malicious code, using Windows native binaries documented by the LOLBAS project. If confirmed malicious, this behavior could indicate lateral movement, allowing attackers to execute code remotely, potentially leading to further compromise and persistence within the environment.
This analytic detects suspicious modifications to Windows firewall rules via the registry. Specifically, it looks for changes that allow inbound traffic on any port with a public profile. This activity is significant as it may indicate an adversary attempting to grant remote access to a machine by modifying firewall rules, potentially leading to unauthorized remote access, further exploitation, data exfiltration, or lateral movement within the network.
The analytic identifies spikes in the number of Server Message Block (SMB) connections using the Machine Learning Toolkit (MLTK). It leverages the Network_Traffic data model to monitor SMB traffic on ports 139 and 445, applying a machine learning model to detect anomalies. Sudden increases in SMB traffic can indicate lateral movement or data exfiltration attempts by attackers. If confirmed malicious, this behavior could lead to unauthorized access, data theft, or further compromise of the network.
The analytic identifies suspicious Java classes often used for remote command execution exploits in Java frameworks like Apache Struts. It detects this activity by analyzing HTTP POST requests with specific content patterns. This behavior is significant because it may indicate an attempt to exploit vulnerabilities in web applications, potentially leading to unauthorized remote code execution. If confirmed malicious, this activity could allow attackers to execute arbitrary commands on the server, leading to data breaches, system compromise, and further network infiltration.
The following analytic detects a process accessing the winlogon.exe system process, indicative of the Rubeus tool attempting to export Kerberos tickets from memory. This detection leverages Sysmon EventCode 10 logs, focusing on processes obtaining a handle to winlogon.exe with specific access rights. This activity is significant as it often precedes pass-the-ticket attacks, where adversaries use stolen Kerberos tickets to move laterally within an environment. If confirmed malicious, this could allow attackers to bypass normal access controls, escalate privileges, and persist within the network, posing a severe security risk.
This analytic detects a single source computer authenticating to 30 or more remote endpoints within a 5-minute timespan using Windows Event ID 4624 (successful logon). This behavior is identified by analyzing Windows Event Logs for LogonType 3 (network logon) events and counting unique target computers. Such activity is significant as it may indicate lateral movement or network share enumeration by an adversary. If confirmed malicious, this could lead to unauthorized access to multiple systems, potentially compromising sensitive data and escalating privileges within the network.
The analytic detects a Kerberos Ticket Granting Ticket (TGT) request using RC4-HMAC encryption (type 0x17) by leveraging Event 4768. This encryption type is outdated and its presence may indicate an OverPass The Hash attack. Monitoring this activity is crucial as it can signify credential theft, allowing adversaries to authenticate to the Kerberos Distribution Center (KDC) using a stolen NTLM hash. If confirmed malicious, this could enable unauthorized access to systems and resources, potentially leading to lateral movement and further compromise within the network.
The following analytic detects the use of Mimikatz command line parameters associated with pass-the-ticket attacks. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line patterns related to Kerberos ticket manipulation. This activity is significant because pass-the-ticket attacks allow adversaries to move laterally within an environment using stolen Kerberos tickets, bypassing normal access controls. If confirmed malicious, this could enable attackers to escalate privileges, access sensitive information, and maintain persistence within the network.
The following analytic identifies unauthorized software downloads to network devices via TFTP, FTP, or SSH/SCP. It detects this activity by analyzing network traffic events on specific ports (69, 21, 22) from devices categorized as network, router, or switch. This activity is significant because adversaries may exploit netbooting to load unauthorized operating systems, potentially compromising network integrity. If confirmed malicious, this could lead to unauthorized control over network devices, enabling further attacks, data exfiltration, or persistent access within the network.
The following analytic identifies a suspicious modification of the Windows registry setting for max connections per server. It detects changes to specific registry paths using data from the Endpoint.Registry datamodel. This activity is significant because altering this setting can be exploited by attackers to increase the number of concurrent connections to a remote server, potentially facilitating DDoS attacks or enabling more effective lateral movement within a compromised network. If confirmed malicious, this could lead to network disruption or further compromise of additional systems.
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