Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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The following analytic identifies potential phishing attempts blocked by Zscaler within a network. It leverages web proxy logs to detect actions tagged as HTML.Phish. The detection method involves analyzing critical data points such as user, threat name, URL, and hostname. This activity is significant for a SOC as it serves as an early warning system for phishing threats, enabling prompt investigation and mitigation. If confirmed malicious, this activity could indicate an attempt to deceive users into divulging sensitive information, potentially leading to data breaches or credential theft.
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.
The following analytic detects the high-frequency exfiltration of archive files via HTTP POST requests. It leverages HTTP stream logs to identify specific archive file headers within the request body. This activity is significant as it often indicates data exfiltration by APTs or trojan spyware after data collection. If confirmed malicious, this behavior could lead to the unauthorized transfer of sensitive data to an attacker’s command and control server, potentially resulting in severe data breaches and loss of confidential information.
Detects network connections from web browsers to domains associated with the UNC5142 EtherHiding technique, including a specific blockchain node and malicious Cloudflare Pages domains.
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.
This detection identifies potential exploitation of a critical SQL injection vulnerability in Ivanti Endpoint Manager (EPM), identified as CVE-2024-29824. The vulnerability, which has a CVSS score of 9.8, allows for remote code execution through the `RecordGoodApp` function in the `PatchBiz.dll` file. An attacker can exploit this vulnerability by manipulating the `goodApp.md5` value in an HTTP POST request to the `/WSStatusEvents/EventHandler.asmx` endpoint, leading to unauthorized command execution on the server. Monitoring for unusual SQL commands and HTTP requests to this endpoint can help identify exploitation attempts. Note that, the detection is focused on the URI path, HTTP method and status code of 200, indicating potential exploitation. To properly identify if this was successful, TLS inspection and additional network traffic analysis is required as the xp_cmdshell comes in via the request body.
The following analytic identifies potential exploitation of the WordPress Bricks Builder plugin RCE vulnerability. It detects HTTP POST requests to the URL path "/wp-json/bricks/v1/render_element" with a status code of 200, leveraging the Web datamodel. This activity is significant as it indicates an attempt to exploit CVE-2024-25600, a known vulnerability that allows remote code execution. If confirmed malicious, an attacker could execute arbitrary commands on the target server, leading to potential full system compromise and unauthorized access to sensitive data.
This analytic detects suspicious downloads from common file sharing and content delivery platforms using known living-off-the-land binaries (LOLBins) such as 'curl.exe', 'certutil.exe', 'msiexec.exe', 'powershell.exe', 'wmic.exe', and others. It leverages Cisco Network Visibility Module logs to correlate network flow activity with process context, including command-line arguments, process path, and parent process information. These tools are often abused by adversaries and malware to retrieve payloads from public hosting platforms such as GitHub, Discord CDN, Transfer.sh, or Pastebin. This detection helps identify potential initial access, payload staging, or command and control activity using legitimate services.
The following analytic detects MSIExec making network connections over ports 443 or 80. This behavior is identified by correlating process creation events from Endpoint Detection and Response (EDR) agents with network traffic logs. Typically, MSIExec does not perform network communication to the internet, making this activity unusual and potentially indicative of malicious behavior. If confirmed malicious, an attacker could be using MSIExec to download or communicate with external servers, potentially leading to data exfiltration, command and control (C2) communication, or further malware deployment.
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 execution of RAR utilities to archive files on a system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, GUIDs, and command-line arguments. This activity is significant as threat actors, including red-teamers and malware like DarkGate, use RAR archiving to compress and exfiltrate collected data from compromised hosts. If confirmed malicious, this behavior could lead to the unauthorized transfer of sensitive information to command and control servers, posing a severe risk to data confidentiality and integrity.
The analytic detects potential data exfiltration using plain HTTP POST requests. It monitors network traffic logs, specifically the `stream_http` data source, for POST methods containing suspicious form data such as "wermgr.exe", "svchost.exe", "name=\"proclist\"", "ipconfig", "name=\"sysinfo\"", or "net view". This activity is commonly associated with malware like Trickbot, trojans, keyloggers, or APT adversaries, which use plain text HTTP POST requests to communicate with remote C2 servers. If confirmed malicious, this activity could lead to unauthorized data exfiltration, compromising sensitive information and potentially leading to further network infiltration.
Detects a potential Oracle E-Business Suite (EBS) authentication bypass attempt, associated with the exploitation of CVE-2025-61882. This activity involves an HTTP POST request to the '/OA_HTML/SyncServlet' endpoint, which is the initial step observed in the exploit chain used by threat actors like GRACEFUL SPIDER.
Detects a variety of HTTP exploitation attempts associated with the RondoDox botnet campaign. This campaign uses a 'shotgun' approach, targeting numerous vulnerabilities in internet-facing devices like routers, DVRs, and web servers.
This rule detects VPN connections originating from countries that are not the user's usual work country. It leverages VPN logs, specifically Zscaler VPN logs, to identify active connections and compares the source IP's country with a lookup of the user's expected work country. Alerts are generated when a mismatch is found, indicating a potentially unauthorized or suspicious access attempt.
Detects potential exploitation attempts against FortiWeb CVE-2025-52970. The detection looks for individual HTTP GET requests to a specific API endpoint with a crafted APSCOOKIE_FWEB cookie containing 'Era=9'. The rule enriches alerts with information about known malicious IPs without strictly filtering on them.
Detects connections to interplanetary file system (IPFS) containing a user's email address which mirrors behaviours observed in recent phishing campaigns leveraging IPFS to host credential harvesting webpages.
Detects attempts to exploit multiple vulnerabilities (CVE-2025-52905, CVE-2025-52906, CVE-2025-52907) in TOTOLINK X6000R routers. Attackers can leverage argument injection, unauthenticated command injection, and security bypasses through the '/cgi-bin/cstecgi.cgi' endpoint to achieve remote code execution or denial of service.
This rule detects the presence of Olymp Loader malware by identifying known malicious file hashes (SHA256) and network communication with associated distribution domains. It looks for these indicators across various data sources, normalizing fields for consistent output. The rule aims to identify systems infected with or communicating with Olymp Loader infrastructure.
Detects Acreed infostealer's cryptocurrency clipper activity. This rule identifies when a host first communicates with a known Acreed C2 domain (`trustdomainnet.live`) to fetch malicious wallet addresses, and then communicates with a QR code generation API (`api.zile42o.dev`) used to replace legitimate QR codes with malicious ones.
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