Threat Actors Poses as Korean TV Programs Writer to Trick Victims and Install Malware

Threat Actors Poses as Korean TV Programs Writer to Trick Victims and Install Malware

Threat Actors Poses as Korean TV Programs’ Writer to Trick Victims and Install Malware

Cybersecurity researchers have uncovered a sophisticated campaign where threat actors impersonate writers from major Korean broadcasting networks to distribute malicious documents.

The operation, tracked as Operation Artemis, represents a notable evolution in social engineering tactics by leveraging trusted media personalities to establish credibility with potential victims before delivering harmful payloads.

The campaign demonstrates a multi-stage attack strategy that combines deception with advanced technical evasion methods.

Threat actors contact victims through email communications disguised as legitimate interview requests or professional collaboration opportunities.

The attackers present themselves as established writers from recognized Korean television programs, using authentic-sounding proposals related to North Korean affairs and human rights issues to align with target interests.

This approach proves particularly effective because the topics resonate with academics, journalists, and policy experts who frequently interact with media organizations.

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Genians analysts identified that the malware emerges from malicious HWP documents—Hangul Word Processor files that serve as the standard document format in South Korea.

These poisoned files arrive as attachments masked as interview questionnaires or event guide materials. Once a victim opens the document and clicks embedded hyperlinks, the infection chain initiates silently in the background.

The technical implementation reveals considerable sophistication. The attack leverages DLL side-loading, a technique where legitimate system utilities from Microsoft Sysinternals become unwitting accomplices.

Photo Used in the Steganography Attack (Source - Genians)
Photo Used in the Steganography Attack (Source – Genians)

Threat actors place malicious DLL files alongside legitimate executables, causing Windows to load the corrupted library instead.

Specifically, the malware creates files named version.dll that get loaded by legitimate processes like vhelp.exe and mhelp.exe.

This method evades traditional signature-based security tools because the parent processes appear legitimate to standard antivirus software.

Attack Flow (Source - Genians)
Attack Flow (Source – Genians)

The DLL file employs multiple encryption layers using XOR operations with key values like 0xFA and 0x29 to conceal its true purpose.

Depending on the target system’s capabilities, the malware intelligently selects between standard byte-wise XOR decryption or high-speed SSE (Streaming SIMD Extensions) methods processing 16 bytes simultaneously.

This adaptive approach increases processing speed while maintaining stealth against pattern-matching security systems.

DLL Side-Loading Technical Breakdown

The malware ultimately deploys RoKRAT, a sophisticated data-stealing tool. The infection chain consists of OLE object execution within HWP documents, followed by temporary folder deployment of executable files and malicious DLLs.

The payload undergoes sequential XOR decryption stages before activating as final shellcode.

Forensic analysis revealed the threat actors maintained command-and-control infrastructure through Yandex Cloud services in Russia, with account tokens showing registration dates spanning from October 2023 to February 2025, indicating sustained operational capability.

Detection requires behavioral monitoring through Endpoint Detection and Response solutions rather than conventional file scanning.

Security teams should monitor abnormal DLL loading from temp directories, suspicious child processes spawned from legitimate executables, and outbound connections to cloud infrastructure immediately following document execution.

The campaign underscores how threat actors continue refining their methodologies to exploit trust and technical detection gaps simultaneously.

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