Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,132 detections
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The analytic detects attempts to exploit CVE-2023-35078, a vulnerability in Ivanti Endpoint Manager Mobile (EPMM) versions up to 11.4. It identifies HTTP requests to the endpoint "/mifs/aad/api/v2/authorized/users?*" with a status code of 200 in web logs. This activity is significant as it indicates unauthorized remote access to restricted functionalities or resources. If confirmed malicious, this could lead to data theft, unauthorized modifications, or further system compromise, necessitating immediate action to mitigate potential severe impacts.
The following analytic detects attempts to exploit a remote code execution vulnerability in Juniper Networks devices. It identifies requests to /webauth_operation.php?PHPRC=*, which are indicative of uploading and executing malicious PHP files. This detection leverages the Web data model, focusing on specific URL patterns and HTTP status codes. This activity is significant because it signals an attempt to gain unauthorized access and execute arbitrary code on the device. If confirmed malicious, the attacker could gain control over the device, leading to data theft, network compromise, or other severe consequences.
The analytic detects potential exploitation attempts of the Log4Shell vulnerability (CVE-2021-44228) by analyzing HTTP headers for specific patterns. It leverages the Web Datamodel and evaluates various indicators such as the presence of `{jndi:`, environment variables, and common URI paths. This detection is significant as Log4Shell allows remote code execution, posing a severe threat to systems. If confirmed malicious, attackers could gain unauthorized access, execute arbitrary code, and potentially compromise sensitive data, leading to extensive damage and data breaches.
The following analytic identifies potential exploitation of Windows Exchange servers via ProxyShell or ProxyNotShell vulnerabilities, followed by post-exploitation activities such as running nltest, Cobalt Strike, Mimikatz, and adding new users. It leverages data from multiple analytic stories, requiring at least five distinct sources to trigger, thus reducing noise. This activity is significant as it indicates a high likelihood of an active compromise, potentially leading to unauthorized access, privilege escalation, and persistent threats within the environment. If confirmed malicious, attackers could gain control over the Exchange server, exfiltrate data, and maintain long-term access.
This analytic detects attempts to exploit the ConnectWise ScreenConnect CVE-2024-1708 vulnerability, which allows path traversal attacks by manipulating file_path and file_name parameters in the URL. It leverages the Endpoint datamodel Filesystem node to identify suspicious file system events, specifically targeting paths and filenames associated with ScreenConnect. This activity is significant as it can lead to unauthorized access to sensitive files and directories, potentially resulting in data exfiltration or arbitrary code execution. If confirmed malicious, attackers could gain unauthorized access and control over the host system, posing a severe security risk.
The following analytic detects attempts to exploit CVE-2022-26134, an unauthenticated remote code execution vulnerability in Confluence. It leverages the Web datamodel to analyze network and CIM-compliant web logs, identifying suspicious URL patterns and parameters indicative of exploitation attempts. This activity is significant as it allows attackers to execute arbitrary code on the Confluence server without authentication, potentially leading to full system compromise. If confirmed malicious, this could result in unauthorized access, data exfiltration, and further lateral movement within the network. Immediate investigation and remediation are crucial to prevent extensive damage.
The analytic identifies attempts to inject Log4Shell JNDI payloads via web calls. It leverages the Web datamodel and uses regex to detect patterns like `${jndi:ldap://` in raw web event data, including HTTP headers. This activity is significant because it targets vulnerabilities in Java web applications using Log4j, such as Apache Struts and Solr. If confirmed malicious, this could allow attackers to execute arbitrary code, potentially leading to full system compromise. Immediate investigation is required to determine if the attempt was successful and to mitigate any potential exploitation.
Detects potential exploitation attempts targeting CVE-2025-31324, a critical unauthenticated file upload vulnerability in SAP NetWeaver Visual Composer. This flaw allows remote attackers to send specially crafted POST requests to the /developmentserver/metadatauploader endpoint, enabling arbitrary file uploads—commonly webshells—resulting in full system compromise. The detection looks for HTTP HEAD or POST requests with a 200 OK status to sensitive Visual Composer endpoints, which may indicate reconnaissance or active exploitation. Successful exploitation can lead to attackers gaining privileged access, deploying malware, and impacting business-critical SAP resources. Immediate patching and investigation of suspicious activity are strongly recommended, as this vulnerability is being actively exploited in the wild.
The analytic detects suspicious processes spawned by WinRM (wsmprovhost.exe). It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific child processes like cmd.exe, powershell.exe, and others. This activity is significant as it may indicate exploitation attempts of vulnerabilities like CVE-2021-31166, which could lead to system instability or compromise. If confirmed malicious, attackers could execute arbitrary commands, escalate privileges, or maintain persistence, posing a severe threat to the environment.
The following analytic detects attempts to exploit the Citrix Bleed vulnerability (CVE-2023-4966), which can lead to the leaking of session tokens. It identifies HTTP requests with a 200 status code targeting the /oauth/idp/.well-known/openid-configuration URL endpoint. By parsing web traffic and filtering based on user agent details, HTTP method, source and destination IPs, and sourcetype, it aims to identify potentially malicious requests. This activity is significant for a SOC because successful exploitation can allow attackers to impersonate legitimate users, bypass authentication, and access sensitive data. If confirmed malicious, it could lead to unauthorized data access, network propagation, and critical information exfiltration.
The analytic detects server-side template injection attempts related to CVE-2022-22954 in VMware Workspace ONE. It identifies HTTP GET requests to the endpoint */catalog-portal/ui/oauth/verify* containing the string "freemarker.template.utility.Execute". This activity indicates potential exploitation attempts that could lead to remote code execution, full system compromise, data exfiltration, or lateral movement.
This analytic identifies instances where the CrushFTP service process (crushftpservice.exe) spawns shell processes such as cmd.exe or powershell.exe. This behavior is unusual for CrushFTP during normal operations and could indicate a successful exploitation of vulnerabilities, such as CVE-2025-31161, allowing an attacker to execute arbitrary commands with the privileges of the CrushFTP service.
This analytic detects potential exploitation attempts against Adobe ColdFusion vulnerabilities CVE-2023-29298 and CVE-2023-26360. It monitors requests to specific ColdFusion Administrator endpoints, especially those with an unexpected additional forward slash, using the Web datamodel. This activity is significant for a SOC as it indicates attempts to bypass access controls, which can lead to unauthorized access to ColdFusion administration endpoints. If confirmed malicious, this could result in data theft, brute force attacks, or further exploitation of other vulnerabilities, posing a serious security risk to the environment.
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 following analytic detects potential exploitation attempts against Microsoft SharePoint Server vulnerability CVE-2023-29357. It leverages the Web datamodel to monitor for specific API calls and HTTP methods indicative of privilege escalation attempts. This activity is significant as it may indicate an attacker is trying to gain unauthorized privileged access to the SharePoint environment. If confirmed malicious, the impact could include unauthorized access to sensitive data, potential data theft, and further compromise of the SharePoint server, leading to a broader security breach.
The following analytic detects attempts to exploit the Spring4Shell vulnerability (CVE-2022-22963) by identifying specific URL patterns associated with web shell payloads. It leverages web traffic data, focusing on HTTP GET requests with URLs containing indicators like "tomcatwar.jsp," "poc.jsp," and "shell.jsp." This activity is significant as it suggests an attacker is trying to deploy a web shell, which can lead to remote code execution. If confirmed malicious, this could allow the attacker to gain persistent access, execute arbitrary commands, and potentially escalate privileges within the compromised environment.
The analytic detects HTTP requests containing payloads related to the Spring4Shell vulnerability (CVE-2022-22965). It leverages Splunk Stream HTTP data to inspect the HTTP request body and form data for specific fields such as "class.module.classLoader.resources.context.parent.pipeline.first". This activity is significant as it indicates an attempt to exploit a critical vulnerability in Spring Framework, potentially leading to remote code execution. If confirmed malicious, this could allow attackers to gain unauthorized access, execute arbitrary code, and compromise the affected system.
The following analytic identifies attempts to exploit a critical template injection vulnerability (CVE-2023-22527) in outdated Confluence Data Center and Server versions. It detects POST requests to the "/template/aui/text-inline.vm" endpoint with HTTP status codes 200 or 202, indicating potential OGNL injection attacks. This activity is significant as it allows unauthenticated attackers to execute arbitrary code remotely. If confirmed malicious, attackers could gain full control over the affected Confluence instance, leading to data breaches, system compromise, and further network infiltration. Immediate patching is essential to mitigate this threat.
The analytic identifies attempts to exploit the JetBrains TeamCity Authentication Bypass vulnerability (CVE-2024-27198). It detects suspicious POST requests to the `/app/rest/users` and `/app/rest/users/id:1/tokens` endpoints, which are indicative of attempts to create new administrator users or generate admin access tokens without authentication. This activity is significant as it can lead to full control over the TeamCity server, including all projects, builds, agents, and artifacts. If confirmed malicious, attackers could gain unauthorized administrative access, leading to severe security breaches.
This analytic identifies a Java user agent performing a GET request for a .class file from a remote site. This behavior is significant as it may indicate exploitation attempts, such as those related to CVE-2021-44228 (Log4Shell). If confirmed malicious, an attacker could exploit vulnerabilities in the Java application, potentially leading to remote code execution and further compromise of the affected system.
This analytic detects Log4Shell JNDI payload injections via outbound connections. It identifies suspicious LDAP lookup functions in web logs, such as `${jndi:ldap://PAYLOAD_INJECTED}`, and correlates them with network traffic to known malicious IP addresses. This detection leverages web and network traffic data to identify attempts to exploit the Log4j vulnerability (CVE-2021-44228), which could lead to remote code execution and system compromise.
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