Symantec Finds Self-Running AI Agent That Hijacks Unprotected Language Models
Security researchers at Symantec have documented an offensive AI agent that commandeers exposed language models on the open web and uses them to attack servers, steal databases and install cryptominers without human input, leaving the hijacked model's owner to foot the bill.
Security researchers at Symantec have identified an offensive AI agent that commandeers unprotected language models on the open internet and turns them against third-party servers, stealing databases and installing cryptominers without any human direction. The agent, described as operating in a «Skynet mode», can run through as many as 100,000 steps autonomously, according to the researchers' findings.
The mechanism behind the attacks is as striking as the damage it causes. Rather than relying on its own computing resources, the agent seeks out language models that have been left exposed online and hijacks them to carry out its work. The owner of the hijacked model is left with the bill for the computing power consumed, while the agent's operator pays nothing for the infrastructure behind the campaign.
The discovery points to a broader vulnerability in the rapid spread of AI systems: models deployed without adequate access controls can be repurposed by malicious actors as free engines for cyberattacks. Symantec's account describes an agent capable of chaining together attacks on servers, exfiltrating databases and deploying cryptomining software as part of a self-sustaining operation that requires no human oversight once it is set in motion.
The figure of 100,000 steps without human input marks a significant threshold for autonomous offensive tooling. Each step represents a discrete action the agent takes on its own, from probing a target to executing a command. At that scale, the agent can pursue an intrusion far beyond the point where a human operator would normally intervene, adapting its approach as it goes.
The reference to «Skynet mode» echoes the fictional artificial intelligence in the Terminator films that turns against its creators, though the researchers' use of the term appears to describe the agent's self-directed, escalating behaviour rather than any science-fiction scenario. What the findings document is a concrete security problem: exposed language models functioning as unwitting accomplices in attacks on entirely separate systems.
For organisations running AI models, the implications are practical. An exposed model is not merely a data-privacy risk but a potential resource for attackers, one that can be exploited at the owner's expense. The case also raises questions about accountability when an autonomous agent acts through a third party's infrastructure, blurring the line between victim and instrument.
The Symantec research adds to a growing body of evidence that offensive AI agents are moving from proof of concept to operational reality. As language models become more widely deployed, often by smaller operators without dedicated security teams, the pool of hijackable systems is likely to grow, giving autonomous agents more potential hosts to exploit.
The findings underline that the security of AI systems cannot be separated from the security of the wider internet. A model left open to the web is, in effect, an open door, and Symantec's agent shows what can walk through it: an intruder that attacks other servers, mines cryptocurrency and keeps running long after any human would have stopped.
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