PipeMagic

Fake ChatGPT Desktop App used to deliver PipeMagic Malware

Microsoft finds that a fake ChatGPT Desktop App Delivering PipeMagic Backdoor,a part of sophisticated malware framework. The PipeMagic campaign represents a dangerous evolution in the global cybercrime landscape. The malicious campaign, powered by a new backdoor called PipeMagic, targets multiple industries including IT, finance, and real estate. The PipeMagic attack is centered around CVE-2025-29824, a critical Windows Common Log File System (CLFS) vulnerability

The PipeMagic campaign a malware to technical threat exploiting trust globally

As per Microsoft cybercriminals are disguising malware as widely popular ChatGPT Desktop Application to launch ransomware attacks across the globe.  

PipeMagic’s evolution from malware to technical threat exploiting trust globally

The malware allows hackers to escalate privileges once inside a system, by leveraging the immense popularity of ChatGPT, attackers have successfully weaponized user trust.

Microsoft has linked the operation to Storm-2460, a financially motivated cybercrime group known for deploying ransomware through stealthy backdoors.

PipeMagic is a malware first detected in December 2022 while investigating a malicious campaign involving RansomExx. The victims were industrial companies in Southeast Asia. To penetrate the infrastructure, the attackers exploited the CVE-2017-0144 vulnerability.

The backdoor’s loader was a trojanized version of Rufus, a utility for formatting USB drives. PipeMagic supported two modes of operation – as a full-fledged backdoor providing remote access, and as a network gateway – and enabled the execution of a wide range of commands.

Pipemagic’s technique of attack

PipeMagic also reflects a growing trend where attackers combine fileless malware techniques with modular frameworks.

By running directly in memory, it avoids detection from traditional signature-based tools. The modular design means it can expand its functionality much like commercial software — essentially transforming cybercrime into a scalable business model.

Another key point is the use of cloud infrastructure for command-and-control. By hosting their servers on Azure, the hackers blend into normal enterprise traffic, making malicious communications far less suspicious. This tactic underscores the need for behavioral monitoring instead of relying solely on blacklists.

Microsoft attributes PipeMagic to a financially motivated group known as Storm-2460. This is a warning sign for future attacks in the broader cybersecurity landscape.

PipeMagic’s modus operandi could be an inspiration for future malware families and its modular framework could fuel a wave of ransomware-as-a-service operations. That possibility raises the stakes not just for enterprises but also for small businesses and even government institutions.

The first stage of the PipeMagic infection execution begins with a malicious in-memory dropper disguised as the open-source for chat GPT application project. The threat actor uses a modified version of the GitHub project that includes malicious code to decrypt and launch an embedded payload in memory.

The embedded payload is the PipeMagic malware, a modular backdoor that communicates with its C2 server over TCP. Once active, PipeMagic receives payload modules through a named pipe and its C2 server.

The malware self-updates by storing these modules in memory using a series of doubly linked lists.

These lists serve distinct purposes for staging, execution, and communication, enabling the threat actor to interact and manage capabilities of backdoor throughout its lifecycle.

By offloading network communication and backdoor tasks to discrete modules, PipeMagic maintains a modular, stealthy, and highly extensible architecture, making detection and analysis significantly challenging.

Microsoft Threat Intelligence encountered PipeMagic as part of research on an attack chain involving the exploitation of CVE-2025-29824, an elevation of privilege vulnerability in Windows Common Log File System (CLFS).

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