Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects anomalous bursts of cloud secret or parameter retrieval API calls followed shortly by administrative actions that expose data or credentials (such as bucket policy changes or new key creation). This behavior is consistent with an adversary staging compromised credentials to exfiltrate data or maintain persistence.
This rule detects potentially malicious activity where a Python-based process or a PyInstaller-compiled executable invokes a command shell (cmd.exe, powershell.exe) or command execution via 'os.popen', followed by a network connection to 'api.telegram.org' within a 60-second window. This behavior is often characteristic of malware or tools using Telegram's API as a command-and-control (C2) channel or for data exfiltration.
Detects HTTP POST requests directed to the URI path '/api/credentials' over the non-standard TCP port 8133, which is indicative of AMOS (Atomic macOS) Stealer exfiltrating stolen credentials to a C2 server.
This rule monitors outbound network traffic for the inclusion of a Windows-style hostname pattern (e.g., 'DESKTOP-XXXXXX'), which is often used by stealer malware or RATs to identify victim machines during C2 communication. It explicitly excludes Microsoft licensing traffic to reduce false positives.
Detects outbound network traffic (TLS and HTTP) destined for the Telegram Bot API (api.telegram.org). This pattern is often used by malicious actors for Command and Control (C2) communication, bot notifications, or data exfiltration, leveraging the legitimate Telegram infrastructure to hide malicious activity.
This rule set detects network communication patterns associated with the AnonyMousKIT phishing kit, specifically targeting the exfiltration of captured user credentials to the Telegram Bot API and communication with known phishing panel infrastructure. It monitors for DNS lookups of 'anomkit.shop', established TCP connections to the associated backend relay, and HTTP requests containing specific credential-related keywords directed towards the Telegram API.
This rule detects anomalous network traffic patterns characteristic of the JWR phishing framework. It identifies live, operator-driven exfiltration where an attacker issues specific instruction sequences (e.g., to_card, to_sms, to_2fa) via HTTP polling or WebSockets to facilitate the character-by-character capture of sensitive information like payment card details and OTPs from a victim.
Detects a suspected malicious sequence associated with RatHat activity. The rule identifies a device fetching an injection template configuration from a remote URL, followed by the exfiltration of credentials or form data to specific API endpoints on the same device within a 15-minute window.
This rule detects potential Adversary-in-the-Middle (AiTM) phishing kit exfiltration behavior. It correlates the initial victim geolocation lookup via 'api.ipgeolocation.io' with subsequent data exfiltration to the Telegram Bot API ('api.telegram.org') originating from the same host, indicating an automated sequence where victim context is gathered and then exfiltrated by the phishing kit.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
Detects high-volume file access or download activity by a single user in SharePoint or OneDrive over a 15-minute window. This behavior is indicative of bulk cloud data exfiltration often associated with extortion campaigns.
Detects outbound network traffic from internal hosts to public Telegram Bot API or Slack webhooks, indicative of potential data exfiltration by the npm indexed-btree malware or similar malicious actors utilizing these services for command and control or exfiltration.
Detects sign-ins to Office Home or Office365 applications from unmanaged or unknown devices, followed by an unusual amount or variety of activity within SharePoint Online or OneDrive for Business within a two-hour window. This behavior is indicative of potential unauthorized access or account compromise where an actor is using a non-corporate device to interact with sensitive cloud documents.
This rule detects network traffic originating from internal hosts to Slack's domain that contains hardcoded Slack bot tokens and specific Slack channel IDs associated with a malicious npm supply chain campaign (indexed-btree). This indicates successful exfiltration of sensitive configuration credentials or data to an attacker-controlled Slack environment.
Detects network traffic associated with the malicious npm package 'indexed-btree', which uses the Telegram Bot API to exfiltrate data. The rules monitor for connections to api.telegram.org via HTTPS and identify specific hardcoded bot tokens and chat IDs associated with the malicious campaign.
Detects bulk uploads or downloads of AI/ML artifacts, such as model weights, datasets, and configuration files, to suspected personal or external cloud storage providers. This rule is designed to identify potential unauthorized exfiltration of proprietary AI/ML assets.
Detects anomalous high-volume API requests from a single user/key to AI model inference endpoints. The rule tracks query diversity and total volume within an hour to identify behavior consistent with model extraction or cloning (AML.T0024.002) via systematic input/output pair collection.
Detects outbound HTTP requests to the Telegram Bot API associated with the malicious 'indexed-btree' npm package. The rule specifically monitors for hardcoded Telegram bot tokens and chat IDs used for data exfiltration.
Detects outbound HTTP requests to the Telegram Bot API associated with the malicious 'indexed-btree' npm package. The rule specifically monitors for hardcoded Telegram bot tokens and chat IDs used for data exfiltration.
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