A Chinese-speaking hacker used AI agents to probe websites and break into sites belonging to more than 100 companies, including Deere, SharkNinja and Cummins, according to a Reuters report based on NorForge research. The campaign illustrates how agents can take on long stretches of reconnaissance and intrusion work, but the reported website breaches do not by themselves establish access to each company’s wider network or confirm that data was stolen.
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What the campaign involved
The attacker coordinated the agents with Cairn, an open-source platform for directing AI agents toward a goal. NorForge researcher Snorre Fagerland came across the activity while looking for exposed Cairn installations. He found more than 20 publicly accessible control panels associated with malicious activity, which allowed him to observe agents working with little apparent human involvement.
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The campaign reportedly began on September 25 and attempted to break into more than 1,200 websites across the United States, Canada, Australia and Japan. More than 100 companies’ websites were reportedly breached. Reuters identified Deere, SharkNinja and Cummins among the victims by reviewing the attacker’s activity; NorForge’s public findings did not name them.
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The reported cost—and what it means
Fagerland estimated the campaign used about $5,000 in AI tokens, or roughly $50 for each successful intrusion. Coverage of the investigation also put a successful intrusion at about 23 hours, though the available reporting does not explain whether that figure is an average.
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The reported tool mix included Cairn and appeared to involve DeepSeek and Anthropic’s Claude Code. These figures are estimates of AI usage, not a full accounting of the attacker’s expenses or the cost of the resulting incidents.
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What the findings show—and what they don’t
The key change is the amount of work the agents could handle: rather than only suggesting code or advising an operator, they reportedly spent hours probing targets and attempting intrusions. That can increase the reach of one attacker, even when the agents still require a human to set goals or coordinate the operation.
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There are important limits to what the available reporting establishes. The targets were websites belonging to companies, not necessarily their entire corporate networks. The supplied reporting also leaves the extent of any data extraction unclear, so it would be inaccurate to describe every named company as having suffered confirmed data theft.
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The incident is therefore evidence of a concerning capability, not proof that AI agents can reliably breach any target or that every attempted intrusion succeeded. The most grounded takeaway is that exposed agent-control panels gave a researcher a view into a campaign where AI performed much of the probing and intrusion work at an estimated low token cost.
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