Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential steganography where a payload is embedded within an image file, specifically a JPEG. It triggers when an HTTP response contains JPEG magic bytes (`FF D8 FF`) within the first 3 bytes, and the file size is unusually large (over 1MB), suggesting additional data might be hidden within the image. The rule also includes a threshold to prevent excessive alerts from legitimate large images.
This rule detects when a cloud disk snapshot is created, specifically targeting AWS EC2 'CreateSnapshot' API calls. This activity can be indicative of data exfiltration attempts, where an attacker creates a snapshot of a compromised disk to move data out of the environment.
This rule detects potential keylogger data exfiltration over HTTP POST requests. It specifically looks for HTTP POST requests where the URI contains the string 'keys' (case-insensitive) and the data size is greater than 200 bytes. This combination suggests that a keylogger might be sending captured keystrokes or other sensitive data to a remote server.
This rule detects HTTP requests for the '.env' file, which often contains sensitive environment variables and credentials. An attacker successfully retrieving this file could gain access to critical system information, API keys, database credentials, and other secrets, leading to further compromise. The rule specifically looks for the string '/.env' in the HTTP URI, indicating an attempt to access this configuration file.
This rule detects the exfiltration of AWS temporary credential tokens over HTTP. It specifically looks for HTTP client body content containing both "ASIA" (which is a common prefix for AWS temporary access keys) and "aws_session_token" (the parameter name for the session token). The detection is case-insensitive and targets established HTTP connections where data is flowing from the client to the server.
This rule detects the exfiltration of a GitHub Personal Access Token (PAT) over HTTP. It specifically looks for the string "ghp_" in the client body of HTTP traffic, which is a common prefix for GitHub PATs. The rule is designed to identify instances where a PAT might be sent from an internal network to an external server, indicating potential credential compromise or data exfiltration.
Detects access or creation of files within Google Drive that have credential-related names, indicating potential credential harvesting attempts or unauthorized access to sensitive data. The rule specifically looks for file events such as 'view', 'edit', 'create', or 'access_url' on files whose titles contain keywords commonly associated with credentials (e.g., password, secret, key, token, etc.).
Detects network traffic over TCP port 886, which is specifically used by Atlas RAT for command and control check-ins, plugin downloads, and encrypted data exfiltration in TA4922 campaigns.
Detects network requests associated with FallSpy, an Android spyware utilized by the Russia-nexus threat group GREYVIBE. FallSpy is deployed via fake persona lures and spoofed applications to harvest critical intelligence. While the original YARA rule targets file-based artifacts (e.g., class names like DataCollectorWork), this Sigma rule adapts the logic to focus on the highly reliable exfiltration URL parameters observable in proxy and web gateway logs.
Detects the execution of MEGAsync.exe with the /upload argument, a technique used by NightSpire ransomware operators to exfiltrate staged data to MEGA cloud storage.
Detects co-occurrence of MicrosoftSystem64 binary execution and DNS queries to huggingface.co from the same host within a 5-minute window. MicrosoftSystem64 is a DPRK-attributed (FAMOUS CHOLLIMA / Contagious Interview) multi-platform RAT delivered via malicious npm packages that exfiltrates stolen credentials, screenshots, and wallet data to attacker-controlled HuggingFace datasets. SafeDep confirmed the exfiltration pipeline was actively operating with real victims as of May 28, 2026.
This rule identifies an anomalous surge in network connection attempts to a particular remote IP address. It establishes a baseline of average daily connection counts to each remote IP over the past week. It then compares the current hourly connection count to this baseline, triggering an alert if the current count is more than five times the baseline and surpasses a total of 500 connections within that hour. This could indicate various malicious activities such as data exfiltration, command and control communication, or a denial-of-service attack originating from the monitored environment.
This rule detects attempts to perform a mass device wipe or deletion using Microsoft Intune. It identifies devices that have been wiped or deleted within the last 24 hours and enriches this information with device details such as name, user, OS, and ownership. This can indicate a destructive attack or an attempt to remove evidence.
This rule detects an unusually high number of web search queries (identified by 'search' or 'query' in the URI) originating from a single IP address within a one-hour window. A threshold of 100 or more queries triggers the alert. This behavior could indicate automated activity such as web scraping, reconnaissance, or a denial-of-service attempt against the search functionality.
This rule detects outbound Server Message Block (SMB) communications from internal devices to external (non-private) IP addresses. It specifically looks for connections on ports 137, 138, 139, and 445. The rule then aggregates these events over 10-minute intervals and flags devices that have more than 5 such SMB connections to distinct external IPs, indicating potential data exfiltration or unauthorized external communication.
This rule detects potential Agent Tesla malware activity by correlating process execution with network connections. It looks for processes named 'agenttesla.exe', 'atsvc.exe', or 'atservice.exe' that execute with command-line arguments indicative of data exfiltration (e.g., 'smtp', 'ftp', 'http.post', 'exfil'). The rule then correlates these process events with outbound network connections to non-private IP addresses, flagging instances where multiple process runs and multiple network connections occur within a 30-minute window.
Detects network traffic over TCP port 886, which is specifically used by Atlas RAT for command and control check-ins, plugin downloads, and encrypted data exfiltration in TA4922 campaigns.
Detects Python processes (python.exe, pythonw.exe) making more than 3 connections to public IP addresses. This activity could indicate data exfiltration, command and control communication, or other suspicious network behavior originating from a Python script.
This rule detects attempts to sell or exchange VPN credentials by looking for the keywords "vpn" and "credentials" in the client body of HTTP traffic. This could indicate an attacker attempting to monetize stolen VPN access or an insider threat attempting to leak sensitive access information.
This rule detects bulk scraping of LinkedIn company profiles. It triggers when a client makes 20 or more HTTP requests to 'linkedin.com' with a URI containing '/company/' within a 60-second window. This behavior is indicative of automated tools attempting to extract large amounts of public company data from LinkedIn.
This rule detects HTTP requests to domains associated with corporate intelligence subscription services such as Dun & Bradstreet (dun.com, dnb.com) and Hoovers (hoovers.com). It triggers an alert if a single source IP makes 10 or more such requests within a 60-second window, indicating potential reconnaissance activity.
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