Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects Ollama server errors and failures during model loading operations that may indicate malicious model injection, path traversal attempts, or exploitation of model loading mechanisms to achieve remote code execution. Adversaries may attempt to load specially crafted malicious models or exploit vulnerabilities in the model loading process to execute arbitrary code on the server. This detection monitors error messages and failure patterns that could signal attempts to abuse model loading functionality for malicious purposes.
By default, the Windows guest account is heavily restricted, with limited permissions and access to system resources.
However, if the guest account is activated, it can potentially be used to perform malicious activities such as installing malware, deleting files, stealing data, or even taking control of the system.
However, if the guest account is activated, it can potentially be used to perform malicious activities such as installing malware, deleting files, stealing data, or even taking control of the system.
This detection identifies potentially suspicious usage of sqlcmd.exe, focusing on command patterns that may indicate data exfiltration, reconnaissance, or malicious database operations. The detection looks for both short-form (-X) and long-form (--flag) suspicious parameter combinations, which have been observed in APT campaigns targeting high-value organizations. For example, threat actors like CL-STA-0048 have been known to abuse sqlcmd.exe for data theft and exfiltration from compromised MSSQL servers. The detection monitors for suspicious authentication attempts, output redirection, and potentially malicious query patterns that could indicate unauthorized database access or data theft.
Correlates a delivered PDF attachment with the same user's browser visiting Mir0Auth C2-style paths within 4 hours. Restricted to browser processes and successful connections, excludes dev/code-hosting domains, and matches users by mailbox alias (DeviceInfo LoggedOnUsers holds UserName, not full email).
This rule detects established TLS connections to external domains that exhibit characteristics often associated with phishing campaigns. Specifically, it looks for domain names in the SNI field that contain common brand names (e.g., microsoft, google, paypal) combined with typical login-related keywords (e.g., login, verify, auth) on high-churn or suspicious Top-Level Domains (TLDs) such as .top, .xyz, or .icu.
This rule detects established TLS connections to external domains that exhibit characteristics often associated with phishing campaigns. Specifically, it looks for domain names in the SNI field that contain common brand names (e.g., microsoft, google, paypal) combined with typical login-related keywords (e.g., login, verify, auth) on high-churn or suspicious Top-Level Domains (TLDs) such as .top, .xyz, or .icu.
This rule detects established TLS connections to external domains that exhibit characteristics often associated with phishing campaigns. Specifically, it looks for domain names in the SNI field that contain common brand names (e.g., microsoft, google, paypal) combined with typical login-related keywords (e.g., login, verify, auth) on high-churn or suspicious Top-Level Domains (TLDs) such as .top, .xyz, or .icu.
Detects network activity associated with a malicious NPM package (typosquatting) beaconing to a known C2 server (69.48.229.140) and performing command and control operations, including command polling and data exfiltration, specifically from a Node.js environment.
This rule detects administrative or user activity within Azure via AzureActivity logs and web request patterns in AppServiceHTTPLogs that originate from a predefined list of known malicious IP addresses.
This rule detects established TLS connections to external domains that exhibit characteristics often associated with phishing campaigns. Specifically, it looks for domain names in the SNI field that contain common brand names (e.g., microsoft, google, paypal) combined with typical login-related keywords (e.g., login, verify, auth) on high-churn or suspicious Top-Level Domains (TLDs) such as .top, .xyz, or .icu.
Detects an authentication pattern characteristic of credential compromise, consisting of a burst of failed authentication attempts against an account within a short window, followed immediately by a successful sign-in from an anomalous or new device/location. This pattern is indicative of brute-force or credential spraying followed by successful validation and potential lateral movement.
Detects instances where the Ivanti Sentry service process spawns suspicious child processes (shells, network utilities, or interpreters) while running with root privileges. This behavior is indicative of exploitation of CVE-2026-10520, an OS command injection vulnerability in Ivanti Sentry that enables unauthenticated remote code execution with root permissions.
This rule detects administrative or user activity within Azure via AzureActivity logs and web request patterns in AppServiceHTTPLogs that originate from a predefined list of known malicious IP addresses.
Detects an authentication pattern characteristic of credential compromise, consisting of a burst of failed authentication attempts against an account within a short window, followed immediately by a successful sign-in from an anomalous or new device/location. This pattern is indicative of brute-force or credential spraying followed by successful validation and potential lateral movement.
Detects Server-Side Request Forgery (SSRF) attempts targeting SonicWall SMA1000 WorkPlace endpoints. The rule monitors both HTTP GET query parameters and HTTP request bodies for patterns indicating attempts to redirect the application to internal loopback addresses or local network ranges (e.g., 127.0.0.1, 169.254.169.254, RFC1918 private subnets).
Detects web application server processes (such as IIS, Apache, Tomcat, Java, Nginx, or Node.js) spawning command-line interpreters or system utilities. This behavior is frequently associated with webshell execution or post-exploitation activities following the exploitation of a public-facing application, often seen in VPN or enterprise software compromises.
Detects alerts that reference specific CVEs historically exploited by the threat group QTFY against internet-facing applications, including common vulnerabilities in Pulse Secure, FortiOS, Citrix ADC, Exchange, F5 BIG-IP, Log4Shell, and others, when the alert severity is Medium or High and contains indicators of exploit or initial access.
Detects multiple inbound HTTP requests targeting known vulnerable application paths (e.g., cgi-bin, .env files, actuator gateways, path traversal, WordPress plugins, PHP eval files, and various server administration consoles) from a single source within a short timeframe. This behavior is indicative of an automated scanner or exploit chain attempting to identify and compromise public-facing applications.
This rule detects established TLS connections to external domains that exhibit characteristics often associated with phishing campaigns. Specifically, it looks for domain names in the SNI field that contain common brand names (e.g., microsoft, google, paypal) combined with typical login-related keywords (e.g., login, verify, auth) on high-churn or suspicious Top-Level Domains (TLDs) such as .top, .xyz, or .icu.
This rule detects attempts to exploit CVE-2026-5027 in Langflow by identifying path traversal sequences (such as '../', '..\', or absolute paths) within the query parameters of requests directed to the '/api/v2/files' endpoint.
Detects an authentication pattern characteristic of credential compromise, consisting of a burst of failed authentication attempts against an account within a short window, followed immediately by a successful sign-in from an anomalous or new device/location. This pattern is indicative of brute-force or credential spraying followed by successful validation and potential lateral movement.
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