The rapid integration of AI-assisted coding tools has become a primary target for threat actors, a new report from Google Threat Intelligence Group (GTIG) has warned.
This shift in software development practices has contributed to several large-scale software supply chain compromises in 2025 and early 2026, according to the researchers.
Operational risks to the software ecosystem have increased for a number of reasons. The rapid adoption of various types of large language models (LLMs) into production environments has led to increases in the overall quantity of open-source resources specifically intended for supporting AI use cases, such as model context protocol (MCP) servers.
GTIG also noted that AI assistants have accelerated the speed of software development, which has likely resulted in the reduced scrutiny of third-party packages and dependencies.
The researchers highlighted the activities of a financially-motivated threat actor tracked as UNC6780 in this area. The group has conducted a series of large-scale open source software supply chain compromises targeting ecosystems including PyPI, npm, and Docker Hub.
It primarily targets AI environments and software dependencies for initial access using a range of techniques embedded within its Dustmaker credential stealer malware. This includes extracting tokens from the process memory of GitHub Actions runners, which allows it to publish compromised versions of packages that pass valid AI coding automated trust checks.
Another approach involves Dustmaker dropping or modifying malicious files into hidden project workspace directories for AI coding assistants, which allows the malware to blend into developer “noise” and avoid detection.
Following initial access, UNC6780 has been observed collecting credentials to AI tools, which the actor subsequently sells to other cybercriminal groups.
“The publicity, apparent success, and open-source release of UNC6780 malware will likely spur adversary emulation of these tactics,” GTIG wrote in the report dated September 8.
Attackers Targeting Proprietary AI Data
A range of threat actors, from state-sponsored groups focused on espionage to data extortion gangs, increasingly targeted proprietary AI research and models in Q2 2026.
This targeting went beyond AI labs and frontier AI companies to organizations using AI in critical sectors such as the government, military and healthcare.
In one example of this activity, GTIG has observed a cyber-espionage campaign by a Chinese nation-state actor tracked as UNC6508, which specifically targets proprietary AI research in academic, medical and military research institutions in North America.
Multiple data theft extortion operations were also observed in Q2, in which attackers stole proprietary AI data, including models, skills, prompts, source code and related research, and threatened to release the data publicly if the companies did not pay a ransom demand. This activity affected organizations operating in the technology, healthcare, pharmaceutical and media and entertainment sectors in North America and Europe.
Threat Actors Continue to Experiment with AI
Another trend observed by GTIG in Q2 was threat actors expanding their experimentation with AI tools during attack lifecycles, moving beyond using AI to support malware and tooling development. Notable examples include:
- A Chinese-nexus actor attempted to leverage Gemini to build an automated pentesting framework. The group sought to build an agentic architecture capable of observing target state, reasoning through actions, and executing tasks in unpredictable environments
- A financially-motivated threat actor leveraged an AI-coding chatbot and a set of agent instructions to build an autonomous, multi-agent attack framework. This allowed the group to plan, build and execute a mass credential harvesting campaign in less than six hours after compromising an organization’s cloud infrastructure
- A command-and-control (C2) server hosting an automated reconnaissance and credential management framework dubbed "Recon," designed for offensive agentic harvesting. Shortly after the server was identified by the GTIG, the exposed directory transitioned to a live, production frontend dashboard designed to organize, validate, and manage over 23,800 harvested secrets in real time, including API keys for cloud and AI services
Commenting on the findings, John Hultquist, chief analyst at GTIG, warned: “At this point, we can assume that all threat actors are using AI in some capacity and their operations have benefited. Like everyone else, we’re concerned about the vulnerability problem, but AI is being applied to several other areas, and it will be especially challenging as it is applied agentically, creating a scaled, faster adversary.”
Hultquist added: “Criminals, like the ones who conducted a mass exploitation campaign in just six hours, will gravitate to attacks that are faster than we can respond to.”
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