Ibrahim Saud
@tektrixIndiaCompletionist
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11,679 detections
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Detects phishing attempts leveraging SendGrid infrastructure to send emails that impersonate well-known financial brands. The detection looks for emails with authentication checks passing (SPF/DKIM/DMARC) where the sender domain is suspicious (e.g., .asia or .com not matching the brand) and the volume of such messages suggests an automated campaign.
This rule monitors for two distinct suspicious patterns: first, the interaction between Claude Desktop and the CEF (Chromium Embedded Framework) library, which may indicate unauthorized plugin or extension loading; second, the execution of non-standard binaries initiated by various JetBrains IDE processes located outside of standard program directories, which could indicate process hollowing or unauthorized tool execution.
Detects unauthorized child processes spawned by ScreenConnect client binaries. The rule specifically looks for files created or modified within 60 seconds prior to execution, which is indicative of attackers leveraging an authentication bypass vulnerability (CVE-2026-84869) to transfer and execute malicious payloads via an active remote access session without requiring additional user interaction or authentication.
This rule detects an HTTP GET request for 'static/js/main.js', a specific URI path associated with the JWR phishing framework's client-side engine. This indicates an interaction with a phishing infrastructure hosting malicious redirection or credential harvesting scripts.
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.
Detects network activity associated with the JWR Phishing-as-a-Service (PhaaS) platform. This includes the retrieval of the client-side JavaScript engine (main.js) from lookalike domains related to courier or government services, and subsequent client-side detection of the 'window.__HOST_MODE' flag, which indicates the browser has been primed for a specific phishing scenario.
Detects HTTP requests directed to the Vapi.ai API from potential phishing panels or malicious infrastructure. This behavior is indicative of an attacker leveraging Vapi.ai's conversational AI services to conduct automated voice phishing (vishing) campaigns by initiating calls or managing AI assistants.
Detects specific URI patterns associated with the 'JWR' phishing framework, which relays live operator instructions to capture pages (e.g., requesting CVV, 2FA codes, or PINs). These patterns are indicative of active adversary-in-the-middle phishing sessions.
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.
These rules detect behavioral patterns associated with GhostCode-style anti-analysis, including URI-based gate redirection (turnstile checks), automated client filtering (User-Agent scanning), and UI-based spoofing (tab title masquerading) often used to protect malicious infrastructure from automated analysis tools and bots.
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