Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
67 detections
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Detects potential abuse of Active Directory Certificate Services (AD CS) by monitoring for suspicious command-line activity from 'certreq.exe' and 'certutil.exe' associated with certificate enrollment, submission, or management. It also identifies the staging of certificate-related files (.pem, .pfx, .p12, .crt, .cer, .key) in common user directories.
This rule detects potential Active Directory Certificate Services (AD CS) abuse (specifically ESC1 and ESC8 patterns) by monitoring command-line executions of 'certreq.exe' and 'certutil.exe' that utilize suspicious flags or originate from non-standard administrative processes. This activity is indicative of an attacker attempting to enroll certificates for unauthorized entities or escalate privileges within a Windows domain.
This rule detects potentially malicious activities related to Active Directory Certificate Services (AD CS). It identifies suspicious certificate export commands (certutil, PowerShell), non-privileged processes writing to system certificate stores, and dangerous AD CS enrollment patterns such as Subject Alternative Name (SAN) modifications, often associated with ESC1 privilege escalation techniques.
This rule detects potential Active Directory Certificate Services (AD CS) abuse (specifically ESC1 and ESC8 patterns) by monitoring command-line executions of 'certreq.exe' and 'certutil.exe' that utilize suspicious flags or originate from non-standard administrative processes. This activity is indicative of an attacker attempting to enroll certificates for unauthorized entities or escalate privileges within a Windows domain.
The following analytic detects the use of default or publicly known named pipes associated with Cobalt Strike. It leverages Sysmon EventID 17 and 18 to identify specific named pipes commonly used by Cobalt Strike's Artifact Kit and Malleable C2 Profiles. This activity is significant because Cobalt Strike is a popular tool for adversaries to conduct post-exploitation tasks, and identifying its named pipes can reveal potential malicious activity. If confirmed malicious, this could indicate an active Cobalt Strike beacon, leading to unauthorized access, data exfiltration, or further lateral movement within the network.
This analytic detects suspicious data transfer activities involving the use of the `split` syscall with the `-b` option, which specifies the size of each output file. This technique can be used by attackers to evade detection by breaking large files into smaller parts, bypassing size-based security controls, and facilitating covert exfiltration of sensitive data. By monitoring for unusual or unauthorized use of the `split` syscall with a specified block size, this analytic helps identify potential data exfiltration attempts.
This analytic identifies the bulk creation of ransomware notes (e.g., .txt, .html, .hta files) on an infected machine. It leverages Sysmon EventCode 11 to detect multiple instances of these file types being created within a short time frame (10 seconds). A detection is triggered if 15 or more unique readme paths are observed. This activity is a strong indicator of an active ransomware attack, where the attacker is notifying the victim of the encryption. If confirmed malicious, this behavior could lead to widespread data encryption, rendering critical files inaccessible and potentially causing significant operational disruption.
The following analytic detects suspicious attempts to find credentials stored in password stores, indicating a potential attacker's effort to access sensitive login information. Password stores are critical repositories that contain valuable credentials, and unauthorized access to them can lead to significant security breaches. By monitoring for unusual or unauthorized activities related to password store access, this analytic helps identify potential credential theft attempts, allowing security teams to respond promptly and prevent unauthorized access to critical systems and data.
The following analytic detects the creation of files in the Windows %startup% folder, a common persistence technique. It leverages the Endpoint.Filesystem data model to identify file creation events in this specific directory. This activity is significant because adversaries often use the startup folder to ensure their malicious code executes automatically upon system boot or user logon. If confirmed malicious, this could allow attackers to maintain persistence on the host, potentially leading to further system compromise and unauthorized access to sensitive information.
The following analytic identifies the creation of executables or scripts in suspicious file paths on Windows systems. It leverages the Endpoint.Filesystem data model to detect files with specific extensions (e.g., .exe, .dll, .ps1) created in uncommon directories (e.g., \windows\fonts\, \users\public\). This activity is significant as adversaries often use these paths to evade detection and maintain persistence. If confirmed malicious, this behavior could allow attackers to execute unauthorized code, escalate privileges, or persist within the environment, posing a significant security threat.
This analytic detects the configuration of TFTP services on Cisco IOS devices that could be used to exfiltrate sensitive configuration files. Threat actors like Static Tundra have been observed configuring TFTP servers to make device configuration files accessible for exfiltration after gaining initial access. The detection specifically looks for commands that expose critical configuration files such as startup-config, running-config, and other sensitive system information through TFTP. This activity is particularly concerning as it may represent an attempt to steal credentials, network topology information, and other sensitive data stored in device configurations.
The following analytic detects the creation or connection of anonymous pipes for inter-process communication (IPC) within a Windows environment. Anonymous pipes are commonly used by legitimate system processes, services, and applications to transfer data between related processes. However, adversaries frequently abuse anonymous pipes to facilitate stealthy process injection, command-and-control (C2) communication, credential theft, or privilege escalation. This detection monitors for unusual anonymous pipe activity, particularly involving non-system processes, unsigned executables, or unexpected parent-child process relationships. While legitimate use cases exist—such as Windows services, software installers, or security tools—unusual or high-frequency anonymous pipe activity should be investigated for potential malware, persistence mechanisms, or lateral movement techniques.
The analytic detects potentially suspicious modifications to Windows Audit Policy auditing options registry values. It focuses on changes to specific auditing option values ("CrashOnAuditFail", "FullPrivilegeAuditing", "AuditBaseObjects", "AuditBaseDirectories") within the "HKLM\System\CurrentControlSet\Control\Lsa\" registry key. Such modifications could indicate a threat actor attempting to tamper with audit policy configurations, potentially disabling SACLs (System Access Control Lists) to bypass defenses and facilitate further malicious activities like machine compromise or lateral movement.
This analytic detects the use of the PowerShell Cmdlet `export-certificate` by leveraging Script Block Logging. This activity is significant as it may indicate an adversary attempting to exfiltrate certificates from the local Certificate Store on a Windows endpoint. Monitoring this behavior is crucial because stolen certificates can be used to impersonate users, decrypt sensitive data, or facilitate further attacks. If confirmed malicious, this activity could lead to unauthorized access to encrypted communications and sensitive information, posing a severe security risk.
The analytic detects the use of the PowerShell cmdlet `export-pfxcertificate` by leveraging Script Block Logging. This activity is significant as it may indicate an adversary attempting to exfiltrate certificates from the Windows Certificate Store. Monitoring this behavior is crucial for identifying potential certificate theft, which can lead to unauthorized access and impersonation attacks. If confirmed malicious, this activity could allow attackers to compromise secure communications, authenticate as legitimate users, and escalate their privileges within the network.
Detects when an application exports a certificate (and potentially the private key as well) from the local Windows certificate store.
This analytic detects suspicious modifications to Unix shell configuration files, such as `.bashrc` or `.profile`, which may indicate an attempt to alter system behavior or gain unauthorized access. Unauthorized changes to these files can be used to execute malicious commands, escalate privileges, or hide malicious activities. By monitoring for unusual or unauthorized modifications to shell configuration files, this analytic helps identify potential security threats, allowing security teams to respond quickly and mitigate risks.
The following analytic detects attempts to stop a service on Linux systems. It leverages data from Linux Auditd. This activity is significant as adversaries often stop or terminate security or critical services to disable defenses or disrupt operations, as seen in malware like Industroyer2. If confirmed malicious, this could lead to the disabling of security mechanisms, allowing attackers to persist, escalate privileges, or deploy destructive payloads, severely impacting system integrity and availability.
The following analytic detects the suspicious auditd service stop. This behavior is critical for a SOC to monitor because it may indicate attempts to gain unauthorized access or maintain control over a system. Such actions could be signs of malicious activity. If confirmed, this could lead to serious consequences, including a compromised system, unauthorized access to sensitive data, or even a wider breach affecting the entire network. Detecting and responding to these signs early is essential to prevent potential security incidents.
The analytic detects cloud API calls executed by user roles that have not previously run these commands. It leverages the Change data model in Splunk to identify commands executed by users with the user_type of AssumedRole and a status of success. This activity is significant because new commands from different user roles can indicate potential malicious activity or unauthorized actions. If confirmed malicious, this behavior could lead to unauthorized access, data breaches, or other damaging outcomes by exploiting new or unmonitored commands within the cloud environment.
The analytic detects the creation of cloud compute instances using previously unseen image IDs. It leverages cloud infrastructure logs to identify new image IDs that have not been observed before. This activity is significant because it may indicate unauthorized or suspicious activity, such as the deployment of malicious payloads or unauthorized access to sensitive information. If confirmed malicious, this could lead to data breaches, unauthorized access, or further compromise of the cloud environment. Immediate investigation is required to determine the legitimacy of the instance creation and to mitigate potential threats.
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