Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects HTTP requests to known data broker websites such as Spokeo, Intelius, and BeenVerified. It triggers an alert if 10 or more such requests are observed from a single source IP within a 60-second window. This activity could indicate reconnaissance efforts to gather information about individuals.
This rule detects potential video stream exfiltration over HTTP POST. It specifically looks for HTTP POST requests with a large payload size (greater than 100,000 bytes) and the byte sequence '|52 49 46 46|' at the beginning of the file data, which corresponds to the 'RIFF' header commonly found in multimedia file formats like AVI and WAV. This combination suggests an attempt to upload or exfiltrate video or audio data.
This rule detects a bulk file copy pattern to a removable share over SMB (port 445). It triggers an alert if there are more than 200 SMB 'to_server' flows from a single source within a 60-second window, indicating a high volume of data transfer. This behavior is often associated with data exfiltration or large-scale data movement to external storage.
This rule detects potential data exfiltration to an AWS S3 bucket. It triggers on HTTP PUT requests to 's3.amazonaws.com' with a payload size greater than 10000 bytes. This could indicate an attacker uploading sensitive data from the internal network to an external S3 bucket they control.
WebDAV File Upload Exfiltration
Suricata
This rule detects potential WebDAV file upload exfiltration attempts by monitoring HTTP traffic for the 'PROPFIND' method. It uses a threshold of 10 occurrences within 60 seconds from the same source IP address to identify suspicious activity, indicating a possible attempt to enumerate or exfiltrate files via WebDAV.
This rule detects potential Secure File Transfer Protocol (SFTP) large file exfiltration attempts. It triggers an alert when a TCP connection on port 22 (SFTP) from the home network to any destination transfers a large amount of data (greater than 65000 bytes) to the server. A threshold of 20 such transfers within 60 seconds from the same source IP is set to reduce false positives. The rule specifically looks for the SFTP protocol magic bytes '|00 00 00|' within the first 4 bytes of the payload.
This rule detects large data exfiltration attempts over SMTP Submission (port 587). It triggers an alert if more than 50,000 bytes of data are sent from a single source IP address to a server via SMTP Submission, with a threshold of 5 such events within a 300-second window. This indicates a potential policy violation related to data exfiltration.
This rule detects large attachments being exfiltrated via SMTP. Specifically, it looks for SMTP traffic on port 25, flowing to the server, that contains the 'Content-Transfer-Encoding: base64' header and has a data size greater than 50,000 bytes. This combination suggests a large, base64-encoded file being sent as an email attachment, which could indicate data exfiltration.
This rule detects potential audio stream exfiltration using the Real-time Transport Protocol (RTP). It specifically looks for UDP traffic with a packet size between 160 and 200 bytes, which is characteristic of some RTP audio streams. A threshold of 100 such packets from the same source within 10 seconds triggers the alert, indicating a sustained audio stream.
This rule detects the upload of a PNG image file over HTTP using a POST request. This could indicate an attacker exfiltrating screen captures, which aligns with MITRE ATT&CK technique T1113 (Screen Capture). The rule specifically looks for the HTTP POST method and the PNG file signature (89 50 4E 47) within the file data.
This rule detects the exfiltration of encrypted archives over HTTP POST requests. It specifically looks for HTTP POST methods, the presence of file data, the 'PK' magic bytes indicating a ZIP or similar archive, and a file size greater than 50,000 bytes. This combination suggests an attempt to send a large, potentially encrypted, archive out of the network.
This rule detects devices exhibiting high volume outbound network traffic, specifically more than 10MB of data transferred across more than 100 sessions to a single remote IP address within a one-minute window. This behavior can be indicative of data exfiltration, unauthorized data transfer, or other suspicious network activity.
Detects the creation of email forwarding rules in Google Workspace that direct emails to external domains. This activity can indicate potential Business Email Compromise (BEC) for persistence or insider data exfiltration.
This rule detects a high number of distinct URLs and total network connections originating from a single remote IP address within a one-minute time window. This behavior can be indicative of various malicious activities such as data exfiltration, command and control (C2) communication, or network scanning. The threshold for distinct URLs is set to greater than 100 and total connections greater than 500.
Detects outbound web requests or GitHub API interactions containing the specific description string "Miasma: The Spreading Blight". This string is used as a signature by the Miasma malware (a Shai-Hulud variant involved in the @redhat-cloud-services npm supply chain attack) when creating malicious GitHub repositories to exfiltrate stolen credentials.
This rule detects potential DNS tunneling or data exfiltration by identifying high volumes of DNS queries with unusually long subdomains from a single process on a device. It aggregates DNS connection inspection events, extracts the subdomain length, and then summarizes the count of queries, unique domains, and average subdomain length within a 10-minute window. An alert is triggered if the query count exceeds 100 or if more than 50 unique domains are observed, combined with subdomain lengths greater than 30 characters.
This rule detects instances where a single remote IP address exhibits a high number of idle network events (more than 200 idle events) and a high total number of network events (more than 500 total events) within a one-minute interval. This pattern can be indicative of Command and Control (C2) communication, where an adversary establishes a connection and then waits for commands, or data exfiltration, where data is sent in bursts with idle periods in between. It highlights unusual network communication patterns that might suggest malicious activity.
This rule detects when a device wipe or delete operation is performed via Microsoft Intune. It specifically looks for 'wipe ManagedDevice' or 'Delete ManagedDevice' operations in Intune audit logs within the last 24 hours. The rule is designed to be correlated with other alerts by filtering on a specific ActorUPN, indicating a potential malicious mass device wipe attack.
Detects the export of Microsoft Teams messages, transcripts, recordings, and chat retrieval activities, particularly when performed via the Graph API. This rule identifies suspicious activity by looking for specific operation names in SaaS audit logs from Microsoft Teams and flags user agents commonly associated with automation tools (e.g., python-requests, axios, go-http, curl, wget, powershell, httpx, aiohttp, node) which could indicate post-compromise attackers using stolen tokens to silently export chat history.
This rule detects the creation or modification of Exchange transport rules or inbox rules that forward or redirect emails to external domains. It specifically looks for operations like 'New-TransportRule', 'Set-TransportRule', 'New-InboxRule', 'Set-InboxRule', 'Set-Mailbox', 'UpdateInboxRules', and 'Set-TransportConfig' where the destination is an email address outside of the organization's verified domains. This activity can indicate data exfiltration or an attempt to maintain persistence and collect sensitive information.
Detects the creation or modification of GitHub Actions workflow files designed to dump and exfiltrate repository secrets, a technique observed in the Mini Shai-Hulud supply chain attack. This rule specifically looks for file events in GitHub Actions workflow directories combined with command-line patterns indicative of secret exfiltration or the creation of a specific malicious workflow file ('codeql_analysis.yml') by scripting interpreters.
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