Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This analytic identifies the use of the GCPloit exploitation framework within Google Cloud Platform (GCP). It detects specific GCP Pub/Sub messages with a function timeout of 539 seconds, which is indicative of GCPloit activity. This detection is significant as GCPloit can be used to escalate privileges and facilitate lateral movement from compromised high-privilege accounts. If confirmed malicious, this activity could allow attackers to gain unauthorized access, escalate their privileges, and move laterally within the GCP environment, potentially compromising sensitive data and critical resources.
The analytic detects local file inclusion (LFI) attacks targeting Kubernetes Nginx ingress controllers. It leverages Kubernetes logs, parsing fields such as `request` and `status` to identify suspicious patterns indicative of LFI attempts. This activity is significant because LFI attacks can allow attackers to read sensitive files from the server, potentially exposing critical information. If confirmed malicious, this could lead to unauthorized access to sensitive data, further exploitation, and potential compromise of the Kubernetes environment.
The following analytic detects attempts to exploit CVE-2022-40684, a Fortinet appliance authentication bypass vulnerability. It identifies REST API requests to the /api/v2/ endpoint using various HTTP methods (GET, POST, PUT, DELETE) that may indicate unauthorized modifications, such as adding SSH keys or creating new users. This detection leverages the Web datamodel to monitor specific URL patterns and HTTP methods. This activity is significant as it can lead to unauthorized access and control over the appliance. If confirmed malicious, attackers could gain persistent access, reroute network traffic, or capture sensitive information.
The following analytic detects `spoolsv.exe` writing a `.dll` file, which is unusual behavior and may indicate exploitation of vulnerabilities like CVE-2021-34527 (PrintNightmare). This detection leverages Sysmon EventID 11 to monitor file creation events in the `\spool\drivers\x64\` directory. This activity is significant because `spoolsv.exe` typically does not write DLL files, and such behavior could signify an ongoing attack. If confirmed malicious, this could allow an attacker to execute arbitrary code, escalate privileges, or maintain persistence on the compromised system.
This analytic identifies remote code execution (RCE) attempts targeting F5 BIG-IP, BIG-IQ, and Traffix SDC devices, specifically exploiting CVE-2020-5902. It uses regex to detect patterns in syslog data that match known exploit strings such as "hsqldb;" and directory traversal sequences. This activity is significant because successful exploitation can allow attackers to execute arbitrary commands on the affected devices, leading to full system compromise. If confirmed malicious, this could result in unauthorized access, data exfiltration, or further lateral movement within the network.
This detection identifies potential exploitation of CVE-2025-24813 in Apache Tomcat through the second stage of the attack. This phase occurs when an attacker attempts to trigger deserialization of a previously uploaded malicious session file by sending a GET request with a specially crafted JSESSIONID cookie. These requests typically have specific characteristics, including a JSESSIONID cookie with a leading dot that matches a previously uploaded filename, and typically result in a HTTP 500 error when the exploitation succeeds.
The analytic detects suspicious behavior indicative of ProxyShell exploitation against on-premise Microsoft Exchange servers. It identifies HTTP POST requests to `autodiscover.json` containing `PowerShell` in the URI, leveraging server-side request forgery (SSRF) to access backend PowerShell. Monitoring this activity is crucial as it may indicate an attacker attempting to execute commands or scripts on the Exchange server. If confirmed malicious, this could lead to unauthorized access, privilege escalation, or persistent control over the Exchange environment.
The analytic detects the loading of `msi.dll` by a binary not located in `system32`, `syswow64`, `winsxs`, or `windows` directories. This is identified using Sysmon EventCode 7, which logs DLL loads, and filters out legitimate system paths. This activity is significant as it may indicate exploitation of CVE-2021-41379 or DLL side-loading attacks, both of which can lead to unauthorized system modifications. If confirmed malicious, this could allow an attacker to execute arbitrary code, escalate privileges, or persist within the environment.
This analytic detects suspicious Kerberos Service Ticket (TGS) requests where the requesting account name matches the service name. This behavior is indicative of an exploitation attempt of CVE-2021-42278 and CVE-2021-42287, often referred to as sAMAccountName spoofing. The detection leverages Windows Event ID 4769 from Domain Controllers. Such activity is significant as it may represent an adversary attempting to escalate privileges by impersonating a domain controller, which could lead to complete domain compromise and unauthorized access to sensitive information.
The analytic identifies the execution of rundll32.exe with command-line arguments loading davclnt.dll and the davsetcookie function to access a remote WebDAV instance. This activity is significant as it may indicate an attempt to exploit CVE-2023-23397, a known vulnerability. If confirmed malicious, this could allow an attacker to execute remote code or exfiltrate data, posing a severe threat to the environment.
The analytic detects the execution of Windows shell processes initiated by WinRAR, such as "cmd.exe", "powershell.exe", "certutil.exe", "mshta.exe", or "bitsadmin.exe". This activity is significant because it may indicate exploitation of the WinRAR CVE-2023-38831 vulnerability, where malicious scripts are executed from spoofed ZIP archives. If confirmed malicious, this could lead to unauthorized access, financial loss, and further malicious activities like data theft or ransomware attacks.
The following analytic detects attempts to exploit the CVE-2023-46747 vulnerability, an authentication bypass flaw in F5 BIG-IP's Configuration utility (TMUI). It identifies this activity by monitoring for specific URI paths such as "*/mgmt/tm/auth/user/*" with the PATCH method and a 200 status code. This behavior is significant for a SOC as it indicates potential unauthorized access attempts, leading to remote code execution. If confirmed malicious, an attacker could gain unauthorized access, execute arbitrary code, steal data, disrupt systems, or conduct further malicious activities within the network.
The following analytic detects potential scanning activities within a Kubernetes environment. It identifies unauthorized access attempts, probing of public APIs, or attempts to exploit known vulnerabilities by monitoring Kubernetes audit logs for repeated failed access attempts or unusual API requests. This activity is significant for a SOC as it may indicate an attacker's preliminary reconnaissance to gather information about the system. If confirmed malicious, this activity could lead to unauthorized access to sensitive systems or data, posing a severe security risk.
The analytic identifies potential exploitation of Log4Shell CVE-2021-44228 by correlating multiple MITRE ATT&CK tactics detected in risk events. It leverages Splunk's risk data model to calculate the distinct count of MITRE ATT&CK tactics from Log4Shell-related detections. This activity is significant because it indicates a high probability of exploitation if two or more distinct tactics are observed. If confirmed malicious, this activity could lead to initial payload delivery, callback to a malicious server, and post-exploitation activities, potentially resulting in unauthorized access, lateral movement, and further compromise of the affected systems.
The analytic identifies POST requests targeting specific Ivanti Connect Secure endpoints vulnerable to the SSRF issue (CVE-2024-21893). It focuses on endpoints such as /dana-ws/saml20.ws, /dana-ws/saml.ws, /dana-ws/samlecp.ws, and /dana-na/auth/saml-logout.cgi. The detection filters for POST requests that received an HTTP 200 OK response, indicating successful execution. This activity is significant as it may indicate an attempt to exploit SSRF vulnerabilities, potentially allowing attackers to access internal services or sensitive data. If confirmed malicious, this could lead to unauthorized access and data exfiltration.
The following analytic detects attempts to exploit the F5 BIG-IP iControl REST API vulnerability (CVE-2022-1388) for unauthenticated remote code execution. It identifies suspicious URI paths and POST HTTP methods, along with specific request headers containing potential commands in the `utilcmdargs` field and a random base64 encoded value in the `X-F5-Auth-Token` field. This activity is significant as it targets a critical vulnerability that can allow attackers to execute arbitrary commands on the affected system. If confirmed malicious, this could lead to full system compromise and unauthorized access to sensitive data.
This analytic identifies attempts to exploit the CVE-2023-46805 and CVE-2024-21887 vulnerabilities in Ivanti Connect Secure. It detects GET requests to the `/api/v1/totp/user-backup-code/../../system/system-information` URI, which leverage an authentication bypass to access system information. The detection uses the Web datamodel to identify requests with a 200 OK response, indicating a successful exploit attempt. This activity is significant as it reveals potential unauthorized access to sensitive system information. If confirmed malicious, attackers could gain critical insights into the system, facilitating further exploitation and compromise.
The analytic identifies potential exploit attempts involving command and script interpreters that are blocked by Zscaler. It uses web proxy logs to detect incidents where actions are blocked due to exploit references. The detection compiles statistics by user, threat name, URL, hostname, file class, and filename. This activity is significant as it helps identify and mitigate exploit attempts, which are critical for maintaining security. If confirmed malicious, such activity could lead to unauthorized code execution, privilege escalation, or persistent access within the environment, posing a severe threat to organizational security.
The following analytic detects attempts to exploit the Zerologon CVE-2020-1472 vulnerability via Zeek RPC. It leverages Zeek DCE-RPC data to identify specific operations: NetrServerPasswordSet2, NetrServerReqChallenge, and NetrServerAuthenticate3. This activity is significant because it indicates an attempt to gain unauthorized access to a domain controller, potentially leading to a complete takeover of an organization's IT infrastructure. If confirmed malicious, the impact could be severe, including data theft, ransomware deployment, or other devastating outcomes. Immediate investigation of the identified IP addresses and RPC operations is crucial.
This detection identifies potential exploitation of CVE-2025-24813 in Apache Tomcat through the initial stage of the attack. This first phase occurs when an attacker attempts to upload a malicious serialized Java object with a .session file extension via an HTTP PUT request. When successful, these uploads typically result in HTTP status codes 201 (Created) or 409 (Conflict) and create the foundation for subsequent deserialization attacks by placing malicious content in a location where Tomcat's session management can access it.
The analytic detects outbound network connections from Java processes to default ports used by LDAP and RMI protocols, which may indicate exploitation of the CVE-2021-44228 Log4j vulnerability. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and network traffic logs. Monitoring this activity is crucial as it can signify an attacker’s attempt to perform JNDI lookups and retrieve malicious payloads. If confirmed malicious, this activity could lead to remote code execution and further compromise of the affected server.
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