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Manic Android Malware Exfiltrates Data From Offline Phones via Nearby Infected Devices

The Hacker Newsby @TheHackersNews ()5 min read6 · 3 reads
AI summary · glm-5.3-flashSummaries by Vani AI

ThreatFabric identified Manic, an Android banking malware and spyware targeting Ukrainian and European financial apps with novel offline Wi-Fi mesh data exfiltration via nearby infected devices.

ThreatFabric reported a new Android malware family called Manic combining banking fraud and surveillance capabilities, targeting 169 package IDs across Ukrainian banks, government and identity services, messaging apps, and Russian and European financial institutions. The malware uses phishing sites and dropper apps impersonating utilities for distribution and relies on accessibility services and notification permissions for keylogging, overlays, and remote control. It introduces a store-and-forward relay mechanism that stages encrypted data locally and relays it through nearby infected devices via Wi-Fi Direct, Bluetooth RFCOMM, or BLE GATT, supporting up to four hops when the primary device lacks internet access. Activity dates back to February 2026, with active development through late July.

Key facts
  • Targets 169 app packages including banks, crypto wallets, and messaging apps
  • Novel offline exfiltration relays data through nearby infected devices
  • Uses accessibility services for keylogging and fake overlays
  • Activity traced to February 2026 with active development into late July
  • Supports remote WebRTC device control and location tracking
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From the original article

5 min read at thehackernews.com

A new Android threat codenamed Manic has been observed actively targeting Ukrainian banks, government and identity services, and messaging applications, as well as Russian and European financial institutions, global fintech and cryptocurrency services, and military-focused communications.

The Hacker News

By @TheHackersNews · thehackernews.com

Read the full article at The Hacker News

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.