Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a suspicious sequence of user activity where a device visits a social media platform (Twitter/X) followed shortly by navigation to a Google Doc. This pattern is often consistent with phishing lures where victims are enticed via direct messages or social engineering to open a malicious document hosted on Google Docs.
Detects a suspicious pattern where a user browser visits a Google Document and subsequently initiates a connection to the Telegram Bot API within a short timeframe (10 minutes). This sequence is indicative of malicious Google Apps Scripts embedded in documents attempting to exfiltrate victim information (IP, geolocation, device details) as part of a reconnaissance phase before a ClickFix-style payload delivery.
Detects HTML files utilizing the 'GhostCode' technique to hide malicious phishing redirects. The technique involves a password-protected HTML lure that uses JavaScript (Web Crypto API) to derive an AES-256-GCM key from a user-provided password via PBKDF2, decrypt an embedded ciphertext payload, and dynamically redirect the user to a concealed phishing URL.
Detects potential reconnaissance activities targeting Redis services on port 6379, specifically looking for unauthenticated 'PING' commands and subsequent responses indicating either authentication requirements or an open, unauthenticated instance.
Detects unauthorized modification of system cron files by the redis-server process, indicative of rogue redis replication exploitation, followed by the execution of a cron job associated with the XMRig cryptocurrency miner.
Detects a suspicious sequence where a Python process is spawned by a 'marimo' notebook process, followed immediately by an outbound SSH connection attempt from the same device. This pattern is indicative of automated or scripted lateral movement where a notebook environment is abused as a jump-point for command execution on remote systems.
This rule detects a suspicious sequence of events indicative of a Redis Lua sandbox escape. It monitors for a network connection to Redis (port 6379) followed shortly by the redis-server process reading the system's /etc/passwd file, which is a known indicator of an attempted arbitrary file read via the EVAL command.
Detects outbound network connections to known JWR phishing framework endpoints. The rule identifies suspicious interaction sequences, including initial beaconing via 'addClick' or 'getSyncSettings' followed by exfiltration of sensitive data (payment card info, OTPs) through POST requests to 'the_final_interface' or 'addCvv', or via a specific WebSocket channel pattern.
Detects outbound network requests to VAPI.ai APIs that are associated with the initiation of AI-powered voice agents. This telemetry can indicate the use of automation or malicious scripts, such as those used by AnonyMousKIT to launch persona-based voice phishing (vishing) campaigns.
Detects the AnonyMousKIT vishing activity pattern by monitoring Twilio API call creation events followed by specific status or gather webhook callbacks from the same host within a one-hour window, consistent with automated voice phishing to collect DTMF-entered passcodes.
This rule detects DNS lookups, email URL clicks, and network connections involving lookalike domains that mimic Singaporean government or infrastructure services (e.g., LTA, OneMotoring, ERP, Gov.sg). It employs a regex-based pattern match for common brand-keywords combined with high-risk top-level domains, identifying potential phishing activity associated with the JWR framework that utilizes algorithmically varied, single-suffix rotated lookalike domains.
Detects SVG files containing embedded ECMAScript that executes a client-side redirect to a known AiTM phishing or C2 domain, specifically targeting the Mirage2FA delivery mechanism.
Detects HTML, XHTML, or SVG files used in Mirage2FA phishing campaigns. These files act as stagers by constructing hidden iframes to load remote JavaScript payloads from '/api/xls/' paths, utilizing specific placeholder tokens and obfuscation techniques such as XOR deobfuscation (0xAD) and custom function wrappers.
These rules monitor for suspicious WordPress authentication activity, including brute force and credential spraying attacks targeting XML-RPC endpoints and the standard wp-login.php interface. The rule set includes detections for high-frequency login attempts and subsequent indicators of potential successful authentication.
Detects indicators associated with the exploitation of CVE-2025-3248 in Langflow. The rule identifies anomalous web requests targeting the /api/v1/validate/code endpoint, subsequent suspicious process creation (base64 encoded payloads in Python/shell), and network communication with identified command and control (C2) or data exfiltration IP addresses. It also includes alerts for observed contact with known extortion email addresses.
Detects indicators associated with the exploitation of CVE-2025-3248 in Langflow. The rule identifies anomalous web requests targeting the /api/v1/validate/code endpoint, subsequent suspicious process creation (base64 encoded payloads in Python/shell), and network communication with identified command and control (C2) or data exfiltration IP addresses. It also includes alerts for observed contact with known extortion email addresses.
This rule detects incoming HTTP POST requests to the '/api/v1/validate/code' endpoint of a Langflow instance. The rule specifically looks for a JSON key 'code' containing a large, potentially base64-encoded string, which indicates an attempt to exploit CVE-2025-3248 to achieve unauthenticated remote code execution.
Detects web requests to 'wp-admin/theme-install.php' containing suspicious query parameters that indicate an attempt to force an unauthenticated theme installation via a Cross-Site Request Forgery (CSRF) exploit (Click2Shell). The rule identifies requests with malicious payloads in the 'theme' parameter, specifically looking for indicators that attempt to bypass CSRF protections when originating from an external site or a non-admin session context.
This rule detects instances where the Terraform CLI tool connects to suspected lookalike domains associated with supply chain compromise attempts (e.g., hashicorp-aws[.]com or hashicorp-terraform[.]io) during common initialization or application workflows. It correlates process execution with network connection logs and optionally validates the presence of a related .terraform.lock.hcl file associated with the malicious origin.
This rule detects instances where the Terraform CLI tool connects to suspected lookalike domains associated with supply chain compromise attempts (e.g., hashicorp-aws[.]com or hashicorp-terraform[.]io) during common initialization or application workflows. It correlates process execution with network connection logs and optionally validates the presence of a related .terraform.lock.hcl file associated with the malicious origin.
The following 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.
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