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AI-Based Obfuscated Malicious Apps Evading AV Detection to Deploy Malicious Payload

Posted on November 21, 2025November 21, 2025 By CWS

A brand new wave of malicious Android purposes impersonating a widely known Korean supply service has emerged, that includes superior obfuscation strategies powered by synthetic intelligence.

These apps work to bypass conventional antivirus detection strategies whereas extracting delicate consumer info.

The risk actors behind this marketing campaign have demonstrated subtle information of cell safety vulnerabilities, combining a number of evasion methods to take care of their operation undetected.

The malware marketing campaign depends on a intelligent supply mechanism that disguises itself as a reliable bundle monitoring software.

When customers grant the mandatory permissions, the app shows an interface resembling the actual supply service by connecting to genuine monitoring web sites utilizing randomly generated monitoring numbers.

Metadata of the malicious app (Supply – ASEC)

This social engineering strategy builds belief whereas the applying performs malicious actions within the background, making it significantly harmful for unsuspecting victims.

ASEC safety analysts recognized this malware after detecting repeated distribution patterns throughout varied channels.

The investigation revealed that risk actors utilized AI-enhanced obfuscation strategies to disguise the app’s performance and make reverse engineering considerably harder for safety researchers.

Detection Evasion Via Clever Obfuscation

The technical sophistication of those purposes lies of their obfuscation implementation. The builders utilized AI-powered ProGuard obfuscation, changing all class names, operate identifiers, and variable names into meaningless eight-character Korean textual content strings.

This strategy differs from customary obfuscation as a result of the random Korean characters make pattern-based detection considerably more durable for automated safety instruments.

Permission request (Supply – ASEC)

The useful resource names remained unmodified, indicating a selective obfuscation technique designed particularly to cover the app’s core performance whereas sustaining sufficient structural integrity for it to function usually.

Safety researchers found that after amassing info from contaminated units, the malware exfiltrates information by means of breached reliable web sites repurposed as command-and-control servers.

The risk actors hardcoded C2 server addresses inside blogs hosted on Korean portals, loading them dynamically when the applying launches.

This method creates a further detection barrier as a result of the precise malicious servers seem as benign net site visitors to community monitoring techniques, successfully hiding the info theft operation from safety infrastructure.

The recognized samples included 5 confirmed MD5 hashes, with related URLs pointing to compromised Korean domains used for information exfiltration.

Safety professionals ought to prioritize detecting and blocking these samples throughout their networks whereas implementing stricter software permission controls for supply service apps.

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Cyber Security News Tags:AIBased, Apps, Deploy, Detection, Evading, Malicious, Obfuscated, Payload

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