Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects outbound network traffic (TLS SNI and HTTP requests) directed to the Telegram Bot API endpoint. This behavior is often associated with malware using Telegram as a command-and-control (C2) channel or for the exfiltration of stolen data, credentials, or sensitive information.
Detects network activity associated with a phishing campaign leveraging Cloudflare Workers, identified as 'ARToken'. The rules monitor for specific TLS SNI patterns, HTTP Host headers, and subsequent C2-like behavior involving device code authentication flows (api/device/start and api/device/poll) hosted on 'workers.dev'.
This rule detects interaction between an internal host and the Vapi.ai API, typically used for automating AI-based voice phishing (vishing) calls. It identifies the initiation of a call via POST requests to the Vapi.ai API and subsequent callbacks from Vapi.ai to an attacker-controlled webhook endpoint used for tracking call status.
This rule monitors network, file, and process telemetry for matches against a predefined list of malicious IP addresses, domain names, and file hashes. It flags suspicious network connections to known C2 infrastructure and the presence or execution of known malicious files based on SHA256 and SHA1 indicators.
C2 Ioc Detection
YARA-L
Detects Network, File, or Process events associated with known C2 IOCs
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 network connections (TLS SNI and HTTP requests) to domains associated with the AnonyMousKIT PhaaS (Phishing-as-a-Service) platform. It flags connections to known phishing backend domains and monitors for access to suspicious management dashboard paths commonly utilized by this threat actor for managing phishing orders and communications.
Detects a Redis process connecting to a suspected rogue replication master (using non-standard ports or known malicious IPs) followed by a file modification to a system cron directory. This sequence is indicative of a Redis Rogue Replication exploit where a crafted RDB file is used to achieve persistence by writing a malicious entry to a cron job.
Detects network traffic consistent with the XMRig cryptocurrency mining tool communicating with a Monero mining pool via TLS. The rule identifies specific SNI domains and direct connection attempts to known proxy IP addresses associated with cryptomining activities.
Detects activity associated with a potential RMM (Remote Monitoring and Management) agent communicating with known malicious infrastructure and accessing sensitive files like credentials or IDs. This often indicates an adversary leveraging legitimate RMM tooling for post-compromise activity or exfiltration.
Detects the installation of a potential remote monitoring and management (RMM) agent via common tools like msiexec, nssm, or sc.exe, followed by consistent HTTPS beaconing to domains hosted on Azurewebsites.net. This pattern is indicative of unauthorized remote access tools used for command and control.
Detects high-volume, broad enumeration of sensitive Microsoft Graph API endpoints (users, groups, directory objects, applications, and mail folders) from a single host or user. This behavior is indicative of automated reconnaissance or post-compromise discovery of cloud identity environments.
Detects a sequence where an AWS Secrets Manager secret is retrieved via CloudTrail, followed within 30 minutes by an EDR-monitored process initiating an outbound network connection on a non-standard port (not 80 or 443). This behavior is consistent with an adversary using stolen credentials to pivot into a persistent command-and-control channel.
This rule detects potential smishing or malvertising attacks by monitoring network activity for the download of .apk files from non-reputable domains. It correlates these download attempts with previous browsing behavior on URLs containing specific 'fake app-store' lure patterns (e.g., promotional text like 'Nexus One' or 'Download Now' outside of official marketplaces like Google Play, APKMirror, or APKPure).
Detects endpoint network activity characterized by a host connection to the Telegram Bot API followed by a connection to a Vercel-hosted domain within 30 minutes. This behavior is indicative of a multi-stage infection chain where adversaries use Telegram for command-and-control communication or victim validation, followed by the retrieval of malicious payloads or lures from disposable infrastructure like Vercel.
Detects network beaconing and command-and-control (C2) communication patterns associated with the RatHat Android malware family. The rule identifies registration, shell command check-ins, heartbeat signals, and task fetching activity over HTTP. It uses stateful inspection (flowbits) to correlate device registration with subsequent heartbeat behavior to improve detection fidelity.
Detects outbound HTTP GET requests directed towards FingerprintJS CDN services that are triggered from or referred by pages hosted on disposable platforms such as Vercel or Netlify. This pattern is commonly indicative of evasion gates or bot-fingerprinting lures used in phishing campaigns to profile victim environments before delivering secondary payloads.
Detects the specific network-observable behavior of the JWR client engine. The rule identifies a device loading the engine script (main.js) followed within a short time window by either a fallback redirection to a_index.html or the initiation of a WebSocket connection using a specific obfuscated path pattern associated with JWR command and control.
Detects the initialization stage of a Mirage2FA phishing attack, characterized by the execution of a locally saved HTML file in a web browser, closely followed by an outbound network connection to the ipify.org API for victim IP geolocation and fingerprinting before the malicious sign-in page is rendered.
Detects DNS queries and HTTP requests associated with the OnyxC2 command and control infrastructure, including specific hardcoded domains and suspicious DNS traffic targeting newly-abused top-level domains (.top, .cyou, .lol).
Detects HTTP CONNECT requests to external networks that include Proxy-Authorization headers with Basic authentication. This pattern is indicative of malicious proxy tunneling or unauthorized credential usage for bypassing security controls or establishing command and control channels via a proxy.
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