Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a suspicious sequence of events where a remote access tool (RAT) is installed on a device, followed by significantly elevated and anomalous database query activity performed by the same account over an extended period. The rule utilizes a baseline window to identify deviations from normal query volumes while excluding known service accounts and administrative ETL/BI tasks.
Detects a suspicious sequence of events where a remote access tool (RAT) is installed on a device, followed by significantly elevated and anomalous database query activity performed by the same account over an extended period. The rule utilizes a baseline window to identify deviations from normal query volumes while excluding known service accounts and administrative ETL/BI tasks.
Detects outbound network connections to known SectopRAT C2 infrastructure, specifically targeting the hardcoded IP 98.142.252.140 or the non-standard port 15847 often used for encrypted exfiltration.
Detects outbound HTTP POST requests from an AI agent runtime environment to known external paste-sites, webhook providers, or staging services. This behavior is indicative of a compromise where the AI agent is being manipulated to exfiltrate sensitive API keys, tokens, or configuration secrets to an attacker-controlled endpoint.
Detects malicious JavaScript injection on e-commerce checkout or payment pages designed to harvest sensitive payment card information (PAN, CVV, expiry) and exfiltrate the stolen data to an external endpoint. This behavior is indicative of a digital credit card skimmer (e.g., Magecart style) deployed following a compromise of the web application.
Detects the initialization of cloud synchronization tools like rclone or MEGAsync, accompanied by the creation of configuration files and subsequent high-volume network activity directed toward common cloud storage providers, indicative of unauthorized data exfiltration.
Detects network communication to specific Gusercontent endpoints consistent with malicious browser extensions exfiltrating captured session tokens or cookies. The rule monitors for POST requests containing parameters like leadId, email, and data, often used to transmit stolen authentication material.
Detects anomalous AI inference API activity characterized by high request volume and high input diversity (querying a wide range of input space). This behavior is indicative of a model replication or extraction sweep aimed at exfiltrating model characteristics or intellectual property.
Detects potential data exfiltration from ML inference APIs by identifying responses to untrusted clients containing patterns indicative of memorized PII (SSN, Email, Credit Card) or detecting automated, repeated extraction-style queries.
Detects high-volume outbound transfers of sensitive machine learning artifacts, such as model files, training datasets, and model registries, to unauthorized external destinations like personal email or unmanaged cloud storage. This behavior is indicative of potential intellectual property theft.
Detects a sequence of potentially malicious activity involving the bulk reading or downloading of sensitive AI-related artifacts (model files, datasets), followed by the staging of these files into a compressed archive, and finally an outbound network transfer to an external IP address. This behavior pattern is indicative of data exfiltration of intellectual property.
Detects the granting of high-privilege permissions (e.g., mail.read, files.readwrite) to a newly registered OAuth application (less than 24 hours old), followed by high-volume API activity from that same application within one hour. This behavior is indicative of an illicit OAuth consent grant attack, where an adversary lures a user into granting permissions to a malicious application to maintain persistent access to cloud resources or perform data exfiltration.
Detects a chained sequence of suspicious activity initiated by agentic AI development tools (e.g., Claude Code, Aider, AutoGen). The rule identifies the execution of these tools followed by local reconnaissance commands, lateral movement attempts, and outbound network connections originating from the same host, indicating potential automated exploitation or credential abuse.
Detects a chained sequence of suspicious activity initiated by agentic AI development tools (e.g., Claude Code, Aider, AutoGen). The rule identifies the execution of these tools followed by local reconnaissance commands, lateral movement attempts, and outbound network connections originating from the same host, indicating potential automated exploitation or credential abuse.
Detects network communication to specific Gusercontent endpoints consistent with malicious browser extensions exfiltrating captured session tokens or cookies. The rule monitors for POST requests containing parameters like leadId, email, and data, often used to transmit stolen authentication material.
Detects anomalous, high-volume activity in cloud-based services such as SharePoint, OneDrive, and Exchange, specifically tracking file access, downloads, and mailbox exports. This behavior may indicate bulk data collection, unauthorized exfiltration, or malicious data staging by a compromised account.
Detects a suspicious sequence of events where a host performs multiple reconnaissance-style probes (health checks, documentation, or OpenAPI definitions) followed within 10 minutes by access to sensitive artifact-related URLs on the same remote host. This pattern is indicative of an attacker profiling a target server for metadata and then proceeding to exfiltrate files or sensitive artifacts.
Detects a suspicious sequence of events where a host performs multiple reconnaissance-style probes (health checks, documentation, or OpenAPI definitions) followed within 10 minutes by access to sensitive artifact-related URLs on the same remote host. This pattern is indicative of an attacker profiling a target server for metadata and then proceeding to exfiltrate files or sensitive artifacts.
Detects the creation of an email inbox rule that includes both a concealment/deletion action and an external forwarding destination, occurring within 4 hours of a high-risk or compromised device-code authentication event. This pattern is indicative of account takeover where an attacker establishes persistence and exfiltration while hiding their activity.
Detects the creation of an email inbox rule that includes both a concealment/deletion action and an external forwarding destination, occurring within 4 hours of a high-risk or compromised device-code authentication event. This pattern is indicative of account takeover where an attacker establishes persistence and exfiltration while hiding their activity.
Detects a specific multi-stage exfiltration pattern characterized by initial reconnaissance/fingerprinting probes against sensitive service endpoints (/health, /docs, /openapi.json) followed by unauthorized access to artifact storage endpoints (/files or /file?name=) from the same device against the same host within a short timeframe.
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