Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects network connections to command-and-control infrastructure associated with the JeetBot/Twitch Enhanced Viewer malicious browser extension. The rule triggers on connections to known malicious domains or IPs, as well as specific API endpoints on ambiguous domains that are used for exfiltrating Twitch OAuth tokens.
Detects network connections to command-and-control infrastructure associated with the JeetBot/Twitch Enhanced Viewer malicious browser extension. The rule triggers on connections to known malicious domains or IPs, as well as specific API endpoints on ambiguous domains that are used for exfiltrating Twitch OAuth tokens.
Detects network connections to command-and-control infrastructure associated with the JeetBot/Twitch Enhanced Viewer malicious browser extension. The rule triggers on connections to known malicious domains or IPs, as well as specific API endpoints on ambiguous domains that are used for exfiltrating Twitch OAuth tokens.
Detects network connections to command-and-control infrastructure associated with the JeetBot/Twitch Enhanced Viewer malicious browser extension. The rule triggers on connections to known malicious domains or IPs, as well as specific API endpoints on ambiguous domains that are used for exfiltrating Twitch OAuth tokens.
Detects network connections to JeetBot/Twitch Enhanced Viewer malicious browser extension infrastructure exfiltrating Twitch OAuth tokens. Apex domains (jeetbot.cc, api.jeetbot.cc) are gated on a token-forwarding indicator to avoid false positives.
Detects anomalous GitHub activity where a single actor interacts with 20 or more unique repositories within a 24-hour period. This behavior is indicative of potential repository scraping, unauthorized data harvesting, or mass configuration changes associated with reconnaissance or exfiltration activity.
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 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, 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 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.
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 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.
Detects anomalous, high-volume file access or download operations in SharePoint from a user agent identified as 'python-httpx'. This behavior is characteristic of automated scripts or potential data exfiltration attempts targeting cloud-based file storage.
Detects high-volume file access and download operations in SharePoint Online and OneDrive where the user agent is identified as 'python-httpx'. This behavior is indicative of automated exfiltration scripts potentially used in malicious cloud intrusion campaigns.
Detects outbound network traffic from internal hosts to the Microsoft Graph API (graph.microsoft.com) originating from Python HTTP clients (requests or urllib libraries). This pattern can indicate automated data exfiltration from an internal environment to a cloud-based service, or the use of Microsoft Graph API for command and control purposes.
Detects high-volume access to Exchange Online mailboxes by a single user from a single IP address using the 'One Outlook Web' application ID, potentially indicating unauthorized automated mailbox data exfiltration.
Detects outbound network traffic (HTTPS and TLS) directed at the specific S3-compatible object storage host 'ams1.vultrobjects.com'. This pattern is associated with 'HEAVYGRAM', a threat actor or toolkit using Vultr S3 buckets for potential data exfiltration.
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.
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 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 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.
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