Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential command injection attacks targeting the Zimbra 'swatchdog' service, specifically involving the abuse of SNMP trap notifications (CVE-2026-73570). The attack works by injecting malicious shell metacharacters into the 'zimbra-MIB::zmServiceName' argument, which is processed by a Perl-invoked 'swatchdog' script. The rule monitors process execution events for shell commands spawned by the swatchdog utility that contain suspicious shell operators and the targeted MIB parameter.
This rule detects potential command injection attacks targeting the Zimbra 'swatchdog' service, specifically involving the abuse of SNMP trap notifications (CVE-2026-73570). The attack works by injecting malicious shell metacharacters into the 'zimbra-MIB::zmServiceName' argument, which is processed by a Perl-invoked 'swatchdog' script. The rule monitors process execution events for shell commands spawned by the swatchdog utility that contain suspicious shell operators and the targeted MIB parameter.
Detects instances where a browser extension is installed, followed within a two-hour window by the browser process making network connections to generative AI service domains. This behavior is indicative of potential malicious browser extension activity, such as scraping or exfiltrating session/browsing data to third-party AI backend services.
This rule detects anomalous increases in inbound network connection volume or unique remote IP address counts associated with a specific process running on a Linux host. This behavior can be indicative of automated scanning, brute-forcing attempts, or a Denial of Service (DoS) attack targeting an exposed API service.
Detects container runtime processes (e.g., docker, podman, crictl) launching containers with elevated privilege flags (such as --privileged, --net=host, or mounting the host root directory) or pulling images from non-standard IP-based registries. These activities are indicative of potential container escapes, persistence mechanisms, or the use of untrusted/malicious container images.
Detects network connections or DNS resolutions to known anonymous file-sharing, cloud storage, and messaging-bot API endpoints (e.g., transfer.sh, Telegram Bot API, Discord CDN) commonly abused by adversaries for data staging and exfiltration. This rule specifically targets non-browser processes that attempt to communicate with these endpoints, helping identify potentially malicious exfiltration activities.
Detects the creation or modification of SSH authorized_keys or authorized_keys2 files. This is a common persistence technique used to maintain remote access by adding an adversary-controlled public key to a user's configuration, often performed after initial access through exploitation of public-facing services.
This rule identifies suspicious post-exploitation activity where an anomalous or unauthenticated NetScaler VPN session (potentially exploiting CVE-2026-88771 or CVE-2026-88772) is followed by the creation or modification of SSH authorized_keys files or related credential manipulation commands on internal hosts, suggesting an attacker establishing persistence.
This rule detects potential credential stuffing attacks by monitoring high-volume authentication attempts against web application login endpoints. It specifically flags scenarios where a high number of unique source IP addresses interact with a login endpoint (e.g., /login, /signin) within a short window, which is characteristic of automated, distributed credential stuffing tools using proxy networks to rotate IPs.
Detects HTTP requests containing common web exploit patterns (SQLi, XSS, RCE) that exhibit characteristics of automated, mutating payload generation often utilized in AI-assisted fuzzing or vulnerability scanning tools. The rule monitors for encoded, obfuscated, or highly varied payload syntax within URI query strings.
Detects unauthorized attempts to access the Ray Dashboard Job Submission API, which is vulnerable to remote code execution (CVE-2023-48022). Attackers can leverage this API endpoint to execute arbitrary commands on the Ray cluster.
Detects inbound HTTP POST requests to the /generate endpoint of a Hugging Face Text Generation Inference (TGI) server. Such requests indicate attempts to use or interact with the inference API, potentially without authentication, which could lead to unauthorized resource utilization or model interaction if the service is not properly secured.
Detects high-frequency outbound network connections to known large language model (LLM) API providers (OpenAI, xAI, Anthropic) originating from a single endpoint within a short timeframe. This activity is indicative of potential API key theft, where an attacker uses a compromised legitimate key to exhaust credit quotas or exfiltrate data via unauthorized API calls, bypassing the intended application.
Detects the creation of web scripts (aspx, php, jsp) in typical web server directories followed by suspicious shell activity (cmd, powershell, or shell execution) originating from web server processes within a 10-minute window. This behavior is indicative of a web shell being dropped and subsequently utilized for command execution.
This rule identifies installations of TeamViewer software that are vulnerable to specific CVEs (CVE-2026-19743, CVE-2026-92368, CVE-2026-92369, CVE-2026-92370, CVE-2026-92371) by analyzing the 'DeviceTvmSoftwareInventory' dataset. It checks for versioning patterns against known vulnerable build numbers across Windows, Linux, and macOS platforms to pinpoint systems requiring patching.
This rule identifies installations of TeamViewer software that are vulnerable to specific CVEs (CVE-2026-19743, CVE-2026-92368, CVE-2026-92369, CVE-2026-92370, CVE-2026-92371) by analyzing the 'DeviceTvmSoftwareInventory' dataset. It checks for versioning patterns against known vulnerable build numbers across Windows, Linux, and macOS platforms to pinpoint systems requiring patching.
Detects the creation of application-specific passwords named 'ZimbraWeb' in Zimbra environments. This pattern is associated with potential persistence mechanisms or credential access attempts where an adversary creates a dedicated service or app password to maintain access, as identified in CVE-2025-66376.
Detects the creation of web shell-consistent files (.jsp, .jspx, .php, .cgi) within sensitive web application directories on Cisco Firepower Management Center (FMC) appliances. This rule is designed to identify potential post-exploitation activity associated with the authentication bypass vulnerability CVE-2026-20079, which has been observed being used by various threat actors to deploy web shells.
Detects the installation or execution of known MALFEX malicious packages via npm or Node.js, which are used as entry points for polyglot or disguised payload delivery.
Detects the creation of scheduled tasks (Windows), cron jobs (Linux), or systemd timers where the initiating process is a common scripting or runtime interpreter (e.g., Python, Node.js, PowerShell, Java). This activity is often indicative of persistence mechanisms being established by a compromised agent or script-based process.
This rule detects anomalous spikes in network connections from a device to major LLM provider API endpoints (OpenAI, Azure OpenAI, Anthropic) by establishing a baseline for each device and identifying deviations exceeding a statistical threshold. Such behavior may indicate unauthorized data exfiltration or mass data processing using LLM services.
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