Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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The analytic detects FTP connections initiated by processes located in non-standard installation paths on Windows systems. It leverages Sysmon EventCode 3 to identify network connections where the process image path does not match common directories like "Program Files" or "Windows\System32". This activity is significant as FTP is often used by adversaries and malware, such as AgentTesla, for Command and Control (C2) communications to exfiltrate stolen data. If confirmed malicious, this could lead to unauthorized data transfer, exposing sensitive information and compromising the integrity of the affected host.
Detects M365 Copilot users exhibiting suspicious application usage patterns including multi-location access, abnormally high activity volumes, or access to multiple Copilot applications that may indicate account compromise or automated abuse. The detection aggregates M365 Copilot Graph API events per user, calculating metrics like distinct cities/countries accessed, unique IP addresses, number of different Copilot apps used, and average events per day over the observation period. Users are flagged when they access Copilot from multiple cities (cities_count > 1), generate excessive daily activity (events_per_day > 100), or use more than two different Copilot applications (app_count > 2), which are anomalous patterns suggesting credential compromise or bot-driven abuse.
This rule detects attempts to bypass M365 Copilot's safeguards and extract sensitive or comprehensive information using various social engineering techniques. It specifically looks for keywords in the 'Subject_Title' field of exported eDiscovery prompt logs that indicate requests for classified, proprietary, or bulk data, or attempts to bypass privacy controls. The rule categorizes these attempts by extraction type and assigns severity levels, filtering out low-severity cases to highlight the most critical risks of AI manipulation for data exfiltration.
The following analytic identifies potential data exfiltration using the PowerShell `net.webclient` command with the `UploadString` method. It leverages PowerShell Script Block Logging to detect instances where this command is executed. This activity is significant as it may indicate an attempt to upload sensitive data, such as desktop screenshots or files, to an external or internal URI, often associated with malware like Winter-Vivern. If confirmed malicious, this could lead to unauthorized data transfer, compromising sensitive information and potentially leading to further exploitation of the compromised host.
The analytic detects potential data exfiltration using plain HTTP POST requests. It monitors network traffic logs, specifically the `stream_http` data source, for POST methods containing suspicious form data such as "wermgr.exe", "svchost.exe", "name=\"proclist\"", "ipconfig", "name=\"sysinfo\"", or "net view". This activity is commonly associated with malware like Trickbot, trojans, keyloggers, or APT adversaries, which use plain text HTTP POST requests to communicate with remote C2 servers. If confirmed malicious, this activity could lead to unauthorized data exfiltration, compromising sensitive information and potentially leading to further network infiltration.
The following analytic detects the execution of a PowerShell script designed to capture screen images on a host. It leverages PowerShell Script Block Logging to identify specific script block text patterns associated with screen capture activities. This behavior is significant as it may indicate an attempt to exfiltrate sensitive information by capturing desktop screenshots. If confirmed malicious, this activity could allow an attacker to gather visual data from the compromised system, potentially leading to data breaches or further exploitation.
Detects data leakage and exfiltration attempts targeting Ollama model metadata and configuration endpoints. Adversaries repeatedly query /api/show, /api/tags, and /api/v1/models to systematically extract sensitive model information including architecture details, fine-tuning parameters, system paths, Modelfile configurations, and proprietary customizations. Multiple inspection attempts within a 15-minute window indicate automated exfiltration of valuable intellectual property such as custom model configurations, system prompts, and internal model specifications. This activity represents unauthorized data disclosure that could enable competitive intelligence gathering, model replication, or preparation for advanced attacks against the AI infrastructure.
This analytic detects the creation of specific archived files, 'passff.tar' and 'cookie.tar', which are known indicators of IcedID malware exfiltrating sensitive browser information like history and cookies. The detection leverages Sysmon EventCode 11 to identify these file creations. This activity is critical as it signifies the potential compromise of sensitive user data, which could lead to further exploitation, data breaches, or escalation of attacker presence within the network.
Detects the use of the rclone tool with data transfer commands (copy, move, sync, copyto, moveto) originating from a GoAnywhere server process or common interactive shell processes (cmd.exe, powershell.exe). This activity is highly suspicious and could indicate data exfiltration.
Detects modifications to the Windows Registry by 'OneDrive.exe' when the initiating process command line does not correspond to a legitimate update operation. This could indicate an attempt to establish persistence or modify OneDrive's behavior for malicious purposes, potentially by an adversary using a compromised OneDrive account or malware like CreepyDrive.
Detects Acreed infostealer's cryptocurrency clipper activity. This rule identifies when a host first communicates with a known Acreed C2 domain (`trustdomainnet.live`) to fetch malicious wallet addresses, and then communicates with a QR code generation API (`api.zile42o.dev`) used to replace legitimate QR codes with malicious ones.
Detects a series of Salesforce Object Query Language (SOQL) queries indicative of data reconnaissance and exfiltration, similar to techniques used by UNC6395.
Detects the creation or modification of a GitHub Actions workflow file that attempts to exfiltrate secrets. This pattern is associated with the Shai-Hulud worm, which injects malicious workflows to steal credentials using `toJSON(secrets)` and exfiltrate them using tools like `curl` and `base64`.
Detects PhantomCard, an Android NFC-relay Trojan targeting banking customers in Brazil. It masquerades as a 'card protection' app and relays NFC data from the victim's card to the fraudster's device.
This rule detects a high volume of DNS queries (over 50) from a single source IP to a limited number of destination IPs (2 or less) for non-standard domains. It excludes common legitimate domains like microsoft.com, google.com, apple.com, cloudflare.com, akamai.com, and amazonaws.com, as well as queries to private IP ranges. This pattern can indicate DNS tunneling, data exfiltration, or command and control activity.
Detects outbound network connections to the Telegram API, a technique used by XWorm for command and control (C2) and data exfiltration. The rule specifically looks for connections to "api.telegram.org/bot" and "/sendMessage" paths, originating from suspicious processes like WmiPrvSE.exe or Soundman.exe, or from common user-writable locations.
Detects network connections to the 'webhook.site' domain, which is used as an exfiltration endpoint by the 'Shai-Halud' supply chain attack campaign. The risk score is elevated if the specific malicious URL path is observed.
This detection identifies potentially suspicious usage of Invoke-Sqlcmd PowerShell cmdlet, which can be used for database operations and potential data exfiltration. The detection looks for suspicious parameter combinations and query patterns that may indicate unauthorized database access, data theft, or malicious database operations. Threat actors may prefer using PowerShell Invoke-Sqlcmd over sqlcmd.exe as it provides a more flexible programmatic interface and can better evade detection.
This detection identifies potentially suspicious usage of sqlcmd.exe, focusing on command patterns that may indicate data exfiltration, reconnaissance, or malicious database operations. The detection looks for both short-form (-X) and long-form (--flag) suspicious parameter combinations, which have been observed in APT campaigns targeting high-value organizations. For example, threat actors like CL-STA-0048 have been known to abuse sqlcmd.exe for data theft and exfiltration from compromised MSSQL servers. The detection monitors for suspicious authentication attempts, output redirection, and potentially malicious query patterns that could indicate unauthorized database access or data theft.
The analytic detects headless browser activity accessing mockbin.org or mocky.io. It identifies processes with the "--headless" and "--disable-gpu" command line arguments, along with references to mockbin.org or mocky.io. This behavior is significant as headless browsers are often used for automated tasks, including malicious activities like web scraping or automated attacks. If confirmed malicious, this activity could indicate an attempt to bypass traditional browser security measures, potentially leading to data exfiltration or further exploitation of web applications.
Detects processes potentially related to XillenStealer making outbound network connections or DNS queries for telegram.org. This is indicative of command and control or data exfiltration activity.
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