According to the organization’s statement, the intrusion began with a malicious dataset exploiting two code-execution paths in the platform’s dataset processing so code could be run on a processing worker. The attack then rose to node-level access, enabling the attacker to harvest cluster and cloud credentials before shifting laterally into multiple internal clusters. 

The statement asserts that the attack was carried out by an “autonomous agent framework,” enacting “many thousands of individual actions across a swarm of short-lived sandboxes, with self-migrating command-and-control staged on public services.” 

“This matches the ‘agentic attacker’ scenario the industry has been forecasting,” the statement warns. 

Rohit Valia, CEO of Tumeryk, comments, “Open source model repositories like Hugging Face now represent a meaningful supply chain risk. As adversaries increasingly target training and fine-tuning data rather than source code, organizations need to test open source models for behavioral drift, not just code-level vulnerabilities. An AI trust score gives enterprises a way to verify a model hasn’t been altered and is safe to use, while aligning to frameworks like the Cloud Security Alliances RiskRubric v2 which provide the structured testing methodology.”