Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects GitLab CI/CD pipeline configuration (.gitlab-ci.yml) that sets job artifacts to 'untracked: true' with 'when: always', which publishes every untracked file as a downloadable CI artifact -- the exact misconfiguration that exposed the leaked GitLab token in the GnuTLS incident.
Detects GitLab CI/CD pipeline configuration (.gitlab-ci.yml) that sets job artifacts to 'untracked: true' with 'when: always', which publishes every untracked file as a downloadable CI artifact -- the exact misconfiguration that exposed the leaked GitLab token in the GnuTLS incident.
Detects unauthenticated GET requests to GitLab CI/CD job artifact download endpoints on a public repository, which can expose leaked secrets bundled into build artifacts.
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 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.
Detects periodic screen capture activity performed by Node.js or Electron-based processes, correlated with subsequent outbound network connections to public IP addresses within a short timeframe. This behavior is indicative of the JSCeal malware's surveillance and exfiltration module, where local reconnaissance via screenshotting is followed by data transmission.
This rule monitors Office 365 SharePoint file operations and search queries for patterns indicative of automated discovery and exfiltration of sensitive content. It specifically identifies high-frequency search queries involving wildcard parameters used in SharePoint content indexing, which may suggest an adversary is systematically crawling or enumerating organizational documents.
Detects network activity communicating with Google Drive domains (drive.google.com and www.googleapis.com). This rule monitors outbound traffic, which may indicate the use of Google Drive as a command-and-control (C2) channel or for unauthorized data exfiltration.
Detects the presence of a specific sentinel string 'data.external.telemetry' within Terraform provisioner job logs, which indicates the execution of unauthorized data-collection logic within a compromised or backdoored Terraform module.
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 unauthorized or suspicious automated scraping behavior by identifying periodic, non-interactive tasks that perform high-volume outbound network requests to multiple external hosts. It specifically filters for processes launched via scheduling mechanisms (Task Scheduler, cron) that exhibit indicators of anti-bot or proxy-rotation bypass techniques (such as usage of headless browser tools or proxy-related keywords in command lines). The rule is tuned to ignore legitimate system maintenance, update, and monitoring processes.
This rule detects potentially unauthorized access or large-scale extraction of sensitive RADIUS server configuration and credential databases. It monitors for common database management tools and commands used in conjunction with RADIUS-specific paths, particularly when executed by unexpected processes, during off-hours, or in a manner indicative of bulk data export.
This rule detects potentially unauthorized access or large-scale extraction of sensitive RADIUS server configuration and credential databases. It monitors for common database management tools and commands used in conjunction with RADIUS-specific paths, particularly when executed by unexpected processes, during off-hours, or in a manner indicative of bulk data export.
Detects anomalous access to Microsoft 365 services (OneDrive, SharePoint, Mail) where the user activity is characterized by a high volume of operations (more than 30) across a diverse set of objects (more than 15) within a one-hour window. The detection focuses on activity originating from specific common automation/scripting User-Agents (Microsoft Graph, Python httpx/requests) that deviate from typical, focused service account behavior.
This rule detects suspicious, high-volume file access or download operations in SharePoint and OneDrive. It filters for activities performed by specific user agents commonly associated with automated scripting tools (e.g., python-requests, Microsoft.Graph.Client), which indicates potential automated exfiltration or unauthorized bulk data collection.
Detects potential data exfiltration activity where a host is communicating with the Telegram Bot API. The rule identifies high-frequency connections to api.telegram.org and inspects HTTP URIs for signs of Telegram Bot token usage combined with 'sendDocument' or 'sendPhoto' commands, which are common indicators of malicious exfiltration.
Detects potential data exfiltration activity where a host is communicating with the Telegram Bot API. The rule identifies high-frequency connections to api.telegram.org and inspects HTTP URIs for signs of Telegram Bot token usage combined with 'sendDocument' or 'sendPhoto' commands, which are common indicators of malicious exfiltration.
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 indicators of cross-site scripting (XSS) attacks aimed at stealing web session cookies. The rule covers the injection of malicious scripts into client responses, anomalous CORS preflight responses that could facilitate data exfiltration, and subsequent HTTP callbacks or beaconing containing cookie data to external endpoints.
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.
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