Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects anomalous, large-scale cloning or mirroring of code repositories combined with targeted access to infrastructure-as-code configuration files (e.g., .tfvars, .tfstate) or automated exfiltration of CI/CD build artifacts. This behavior is indicative of an adversary attempting to exfiltrate proprietary source code or sensitive secrets stored within repositories.
Detects the creation of a new AWS S3 bucket followed by a large volume of data uploads (more than 200 objects) within a 2-hour window. The detection focuses on activity attributed to a single identity with limited source IP diversity, which is highly indicative of scripted data staging and potential exfiltration preparation by an unauthorized actor.
Detects Odyssey Stealer malware communicating with a known C2 infrastructure using TLS and performing data exfiltration via HTTP requests to raw-IP destinations using disguised file names such as analytics.gif, pixel.png, and content.js.
This rule detects potential automated cryptocurrency wallet draining activity by correlating the execution of known stealer processes (such as GapiUpdate or NeedleStealer) with subsequent outbound network connections to suspicious command-and-control domains or API endpoints within a 30-minute window.
This rule detects potential exfiltration of sensitive files, specifically 'cert.pem' and 'private.key', via HTTP POST requests to the '/api/adbk/upload' endpoint. This pattern is characteristic of the RatHat malware attempting to exfiltrate device credentials to a Command and Control (C2) server.
Detects HTTP POST requests from Android devices identified as RatHat malware, specifically targeting exfiltration of sensitive data including credentials, cipher keys, and ADB certificate/key uploads via the malware's C2 API.
Detects the creation or modification of Power Automate flows that involve potentially sensitive external services or personal email providers, which may indicate data exfiltration or unauthorized integration setup.
Detects anomalous, high-frequency mailbox search and access activity targeting financial-related keywords (e.g., invoices, wire transfers, bank details). This behavior pattern is frequently observed during business email compromise (BEC) attacks, where adversaries utilize OAuth tokens to triage mailboxes for sensitive payment information.
Detects potential exfiltration activity by identifying HTTP POST/PUT requests to known suspicious domains, including specific operator-controlled hosts and anonymous file sharing services, as well as the use of HTTP Range headers for bulk API data exfiltration.
Detects the creation of a new AWS S3 bucket followed by a large volume of data uploads (more than 200 objects) within a 2-hour window. The detection focuses on activity attributed to a single identity with limited source IP diversity, which is highly indicative of scripted data staging and potential exfiltration preparation by an unauthorized actor.
Detects anomalous high-volume access to Exchange Online via the One Outlook Web/Office client, potentially indicating data exfiltration or automated mass email access by a compromised account.
This rule detects anomalous activity where users access Microsoft 365 services (SharePoint, OneDrive, Exchange) through identified anonymous proxy connections. It identifies potentially malicious exfiltration or bulk activity by flagging users who perform a high number of operations (1,000+ events) or download a significant volume of data (5GB+) within a 2-hour window.
Detects instances where a user or entity accessing a file (download, access, or preview) originates from an IP address identified as an anonymous proxy. This rule is designed to be used with a downstream aggregation tool to identify potentially unauthorized data exfiltration or access via anonymization services.
This rule detects anomalous, high-volume file access or download activity across cloud applications and file storage services. It tracks users over a period of time, flagging individuals whose daily activity consistently contributes to a large total volume of data access (exceeding 500MB) over at least five days, specifically looking for sustained behavior that deviates from sudden, single-day spikes.
This rule detects potentially malicious or automated data access patterns within Microsoft 365 or similar cloud environments. It identifies user accounts or applications that exhibit a high volume of file/email access operations across a diverse set of paths, which is often indicative of automated data exfiltration, scraping, or suspicious collection by a compromised identity.
Detects anomalous data access or collection activity across multiple M365 workloads (SharePoint, OneDrive, Exchange). The rule identifies users exhibiting high volumes of file or mail access across at least two distinct workloads within a one-hour window, which may indicate account compromise, bulk data exfiltration, or unauthorized persistence via mailbox rules.
This rule detects high-volume file access, preview, or download activity from SaaS applications (SharePoint, OneDrive, Exchange Online) originating from IP addresses classified as anonymous proxies. The threshold is set to 1000 events within a 2-hour window, which is indicative of automated, high-speed data exfiltration rather than standard user behavior.
Detects anomalous or high-volume activity related to Microsoft Graph API calls targeting email messages, mail folders, or attachments. This behavior is indicative of potential unauthorized bulk email collection or exfiltration attempts, often observed in account compromise scenarios where an attacker enumerates and downloads mail contents.
Detects anomalous or high-volume activity related to Microsoft Graph API calls targeting email messages, mail folders, or attachments. This behavior is indicative of potential unauthorized bulk email collection or exfiltration attempts, often observed in account compromise scenarios where an attacker enumerates and downloads mail contents.
Detects anomalous, high-volume file access (downloading, accessing, or previewing) in cloud applications that originates from an IP address identified as an anonymous proxy. This behavior is indicative of potential data exfiltration or unauthorized mass data collection.
This rule detects potentially malicious interaction with specific GCP service account identifiers and client IDs. It monitors multiple log sources—including cloud audit logs, sign-in activity, security logs, and device network events—to identify unauthorized access, command and control communication, or data exfiltration attempts targeting Google API services (specifically oauth2.googleapis.com and sheets.googleapis.com).
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