Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
640 detections
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This rule detects network communication with known AI model providers by checking `RemoteUrl` against a list of AI API URLs from an external CSV file. It aims to identify potential unauthorized use of AI services, data exfiltration to AI models, or to monitor AI usage within an environment.
This rule is meant to help analysts quickly spot a high-confidence indicator related to Google ShinyHunters SaaS Defense Guidance. It is written to be easy to understand and to keep false alarms low by focusing on a very specific match: rclone used with copy/sync style commands to move data to a remote destination. A match does not automatically prove an attacker is currently active, and it does not prove a file was executed, but it does mean the event is important because it lines up with a public threat intelligence source. When this triggers, start by identifying the host, user, and timeframe involved, then decide whether the activity is expected for that system. If it is unexpected, preserve the related logs and any files, and look for nearby events that could explain how the indicator appeared, such as a download, a new process, or a new connection. If the same indicator appears on multiple systems, treat it as a scoping signal and expand the investigation window. Use the reference link (https://cloud.google.com/blog/topics/threat- intelligence/defense-against-shinyhunters-cybercrime-saas) to document where the indicator came from and to support incident notes and reporting.
This rule set detects various stages of activity related to the 'OpenClaw' malware family and associated campaigns. It includes detection for OpenClaw process execution, exposure of a specific administrative port, execution of shell commands via curl (ClawHavoc delivery), outbound webhook exfiltration, and infostealer access to OpenClaw configuration files.
Detects action of git clone or git push in a repo where the source actor is not coming from a Corp IP Space. (Add your IP Blocks as needed to the filter)
Detects execution of tools and artefacts reported in Unit 42 Muddled Libra operational playbook, including Chisel tunnelling, PsExec, ADExplorer, S3 Browser, and goon.zip staging.
This rule detects outbound network connections to known Command and Control (C2) and exfiltration domains associated with the SANDWORM_MODE campaign. These domains are used to exfiltrate stolen credentials and other sensitive data.
This rule detects network connections from common web browsers to known command and control (C2) domains associated with the ChatGPT Stealer campaign. These domains are used to exfiltrate stolen AI session tokens and conversation data.
Detects execution of curl.exe uploading data to temp.sh using custom user-agent parameters, consistent with publicly reported malicious Notepad++ updater activity.
Detects programmatic GitHub data exfiltration by identifying non-interactive repository exports, clones, artifact downloads, or gist staging performed using tokens, OAuth applications, or GitHub Apps. The detection focuses on bursty or multi-repository activity within a short time window, which can indicate automated source code collection, misuse of programmatic credentials, or post-compromise data extraction.
This detection identifies network connections from non-browser processes to known Large Language Model (LLM) API endpoints. While some connections may be legitimate developer or application traffic, unexpected processes connecting to these services could indicate unauthorized data exfiltration, corporate espionage, or misuse of AI services.
This rule detects HTTP network connections to the Telegram bot API (api.telegram.org/bot). This pattern is often associated with infostealers exfiltrating data to attacker-controlled Telegram bots. The rule specifically looks for the 'NETWORK_HTTP' event type and a URL containing '/api.telegram.org/bot' (case-insensitive).
Detects the creation or modification of repository webhooks in GitHub. Attackers can use webhooks for real-time data exfiltration of code pushes, pull request comments, and workflow data. Once a webhook is established, it operates independently of the creating user; revoking the creator's credentials will NOT stop the data flow. Only deleting the webhook itself terminates the exfiltration.
Detects outbound network traffic to known infrastructure used in OpenClaw malicious skill delivery or credential exfiltration. These IOCs were identified in the NSFOCUS report on OpenClaw security risks.
Detects file access or download operations from Microsoft SharePoint Online where the User-Agent string indicates the use of PowerShell. This behavior has been observed in campaigns by threat groups for bulk data exfiltration.
Detects instances where an AI agent process (e.g., Moltbot, ClawdBot) performs a web search or HTTP request containing suspicious internal identifiers (like API keys or project names) as URL parameters. This behavior is a hallmark of 'search-and-leak' exfiltration tactics, often triggered by indirect prompt injection.
This rule detects applications, other than common web browsers, that are making network connections to Google Analytics domains and also contain 'microsoft' in the remote URL. This could indicate an application collecting device information or other telemetry and exfiltrating it via Google Analytics, potentially for malicious purposes or unauthorized data collection.
Detects outbound network connections from common web server processes to the Telegram API domain (api.telegram.org). This behavior is indicative of the BlackForce phishing kit exfiltrating stolen credentials, as newer versions use a server-side component to relay data to a Telegram channel.
This rule detects the presence and activity of the ShadyPanda malware campaign, specifically focusing on malicious Chrome extensions and their associated command and control (C2) and data exfiltration domains. It identifies the creation of files with known malicious Chrome extension IDs (ending in '.crx') and network connections to hardcoded C2 and exfiltration domains linked to the ShadyPanda campaign.
This rule detects the presence and activity of the ShadyPanda malware campaign, specifically focusing on malicious Chrome extensions and their associated command and control (C2) and data exfiltration domains. It identifies the creation of files with known malicious Chrome extension IDs (ending in '.crx') and network connections to hardcoded C2 and exfiltration domains linked to the ShadyPanda campaign.
Detects creation of branches and files matching indicators used by Shai-Hulud 2.0 for exfiltration
Detects GitHub Actions activity matching indicators used by Shai-Hulud 2.0 for exfiltration and persistence
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