Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a single user account downloading or accessing a high volume of files (more than 50) within a 15-minute window from SharePoint or OneDrive. This behavior often indicates automated data collection, potential mass exfiltration, or a compromised user account account accessing sensitive files in bulk.
This rule detects network connections and HTTP requests to known malicious URLs, including file downloads associated with C2 infrastructure and malware distribution campaigns. It monitors both direct device network events and HTTP requests logged through security product events to identify potential secondary-stage payload delivery.
Detection of network traffic associated with the delivery of the Rapuncel information stealer. The rules monitor for large ZIP archives masquerading as LastPass Authenticator installers and detect attempts to reach out to external domains for DLL sideloading artifacts (TitanStorage.dll and ProManager.dll).
Detects artifacts, domains, and web content associated with the Rapuncel MaaS phishing campaign. The rule specifically targets HTML/JS markers from fake LastPass Authenticator GitHub Pages sites, which employ social-engineering tactics such as fake trust badges and malicious download prompts to distribute the Rapuncel infostealer.
This rule detects network connections or process command lines associated with known malicious domains, IP addresses, or payload URLs. Additionally, it correlates connections to common public file-sharing platforms or APIs (e.g., Gofile, Telegram) if these events occur on the same device within a 60-minute window of a confirmed malicious infrastructure event, reducing false positives from legitimate uses of shared infrastructure.
Detects rapid, bulk cloning or downloading of GitHub repositories containing sensitive data (e.g., consensus algorithms, PII, internal blocklists). This behavior is characteristic of unauthorized data exfiltration, specifically tracking activity involving suspicious OAuth token prefixes (gho_) and rapid high-volume access to sensitive organizational assets within a short timeframe.
Detects rapid, bulk cloning or downloading of GitHub repositories containing sensitive data (e.g., consensus algorithms, PII, internal blocklists). This behavior is characteristic of unauthorized data exfiltration, specifically tracking activity involving suspicious OAuth token prefixes (gho_) and rapid high-volume access to sensitive organizational assets within a short timeframe.
Detects rapid, bulk cloning or downloading of GitHub repositories containing sensitive data (e.g., consensus algorithms, PII, internal blocklists). This behavior is characteristic of unauthorized data exfiltration, specifically tracking activity involving suspicious OAuth token prefixes (gho_) and rapid high-volume access to sensitive organizational assets within a short timeframe.
Detects rapid, bulk cloning or downloading of GitHub repositories containing sensitive data (e.g., consensus algorithms, PII, internal blocklists). This behavior is characteristic of unauthorized data exfiltration, specifically tracking activity involving suspicious OAuth token prefixes (gho_) and rapid high-volume access to sensitive organizational assets within a short timeframe.
Detects HTTP downloads from GitHub involving specific repositories and archive naming patterns commonly associated with the 'NightEagle GhostContainer' threat activity. These patterns involve downloading ZIP files disguised as development or resource packages (e.g., 'mirror-js', 'browserthemes', 'resource-pack').
Detects HTTP downloads from GitHub involving specific repositories and archive naming patterns commonly associated with the 'NightEagle GhostContainer' threat activity. These patterns involve downloading ZIP files disguised as development or resource packages (e.g., 'mirror-js', 'browserthemes', 'resource-pack').
Detects potential installation of compromised Admin Menu Editor Pro plugin updates by identifying sequential download events for specific plugin versions from the 'adminmenueditor.com' domain within a 24-hour window. This behavior is indicative of a supply chain attack where a legitimate update mechanism is leveraged to deliver malicious payloads without integrity verification.
Detects file access or download operations performed by the python-httpx library within a specific cloud application context, which may indicate automated data retrieval or exfiltration attempts by scripts or custom tools.
Detects malicious PowerShell activity using the -ExecutionPolicy Bypass flag combined with caret obfuscation or indicators related to known malicious infrastructure used in ClickFix-style social engineering campaigns. The rule specifically monitors for attempts to download or execute configuration.ps1 from identified attacker domains and IP addresses.
Detects the creation of files in the /tmp/ directory by common command-line tools (curl, wget, sh, bash), followed shortly by a successful external network connection by the same process from the same device, excluding known benign domains.
This rule detects network connections or process command lines associated with known malicious domains, IP addresses, or payload URLs. Additionally, it correlates connections to common public file-sharing platforms or APIs (e.g., Gofile, Telegram) if these events occur on the same device within a 60-minute window of a confirmed malicious infrastructure event, reducing false positives from legitimate uses of shared infrastructure.
This rule monitors Office 365 file download activity, identifying users whose download volume significantly deviates from their historical baseline. It specifically looks for an unusually high number of unique files downloaded in a one-hour window, while excluding known service accounts and synchronization agents like OneDrive sync client.
This rule detects attempts to download known malicious NPM packages from the public npm registry (registry.npmjs.org) by monitoring network connection logs. It specifically looks for tarball (.tgz) downloads of packages and versions that have been identified as compromised or malicious. The rule extracts the package name and version from the download URL and compares it against a predefined list of malicious packages for high-fidelity detection.
Detects instances where common web server applications (e.g., Apache, Tomcat, IIS, Nginx) or Java runtime environments spawn suspicious child processes like command shells (cmd.exe, powershell.exe, sh, bash) or network utilities (wget, curl). This behavior often indicates exploitation of a web vulnerability, such as Remote Code Execution (RCE), allowing an adversary to execute commands or download further malicious payloads.
Detects instances where PowerShell is used to download an executable named 'svchost.exe' from an external IP address (103.86.86.244). The rule monitors for network connections to this IP, file creation events matching specific download patterns in fonts directories, and direct command-line arguments involving the suspicious IP and file path, indicating potential malware dropper activity.
This rule detects the execution of powershell.exe with command-line arguments that utilize 'curl' to download a file from a specific remote IP address (103.86.86.244). This behavior is characteristic of adversaries using built-in Windows tools or redirected utilities to perform ingress tool transfer as part of a malicious payload delivery.
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