Topic

WebRTC

🇵🇹Aug 21

Manic Android Malware Steals PINs via Transparent Overlay and Relays Data Through Nearby Infected Devices

A newly identified Android malware strain named Manic merges banking trojan, spyware, and remote access capabilities. The threat has been active since at least February 2026 and continues to receive updates that add anti-analysis features, in-memory code loading, and lock-screen credential theft. Manic monitors 169 financial, messaging, and government applications while using a transparent overlay on legitimate numeric keyboards to capture PINs without displaying a full fake banking screen. Stolen data can be forwarded through other compromised nearby devices even when the original phone lacks internet connectivity. Operators also leverage WebRTC sessions for live screen viewing and remote interaction. The malware additionally functions as a keylogger, intercepts SMS and notifications, and collects passwords, one-time codes, and recovery phrases. Security researchers recommend avoiding unknown APKs and scrutinizing requests for Accessibility Services or broad device control permissions.

BoletimSec•Malware & Botnets
🇷🇺Jul 19

Aurorium Anti-Detect Browser Uses AI Fingerprinting Linked to Real Hardware and User Profiles to Evade Modern Anti-Fraud Systems

Aurorium is an anti-detect browser that differentiates itself from competitors by embedding spoofing directly into the browser kernel rather than relying on JavaScript patches. The product generates fingerprints using AI that analyzes the operator’s actual device hardware and matches it to a realistic social profile including age, income, occupation, and geography. Network routing is handled at the kernel level so that WebRTC and DNS traffic is forced through proxies without disabling features that anti-fraud systems flag. The company also published a detailed Cure53 security audit that identified and subsequently fixed four critical vulnerabilities. Team-oriented features include built-in CRM, task management, multi-team support, and a mobile application. The review highlights that Aurorium’s approach reduces the common mismatch between generated fingerprints and the supposed user’s real-world context that often triggers detection.

Securitylab•Fraud & Social Engineering