Skip to header Skip to main navigation Skip to main content Skip to footer

One Hacker, a Few Thousand Dollars, and AI Agents Broke Into More Than 100 Sites

Breadcrumb

  • Home
  • One Hacker, a Few Thousand Dollars, and AI Agents Broke Into More Than 100 Sites

Over the past couple of weeks, a cybersecurity researcher watched a single Chinese-speaking hacker break into websites belonging to more than 100 companies, including farm equipment maker Deere, home appliance company SharkNinja and engine manufacturer Cummins. The hacker did almost none of the work personally. According to Snorre Fagerland, principal threat researcher at NorForge, in a report provided to Reuters ahead of publication on Monday, October 19, the intrusions were outsourced almost entirely to AI agents that spent hours autonomously probing and breaking into targeted sites.

Fagerland found the campaign while scanning the web for inadvertently exposed instances of Cairn, an open-source AI problem-solving platform popular with hackers. Beginning around October 2, he found about two dozen instances of Cairn being used for malicious activity, which let him quietly watch over the criminals' shoulders. The most prolific hacker he observed began on September 25, gave their agents instructions sketched out in fewer than 100 Chinese characters, and set them loose on e-commerce sites in the United States, Canada, Australia and Japan. By late last week the agents had attempted to break into more than 1,200 sites.

The economics are the uncomfortable part. Successful intrusions typically took about 23 hours of automated probing, and Fagerland estimated the campaign, which appeared to use a mixture of DeepSeek models and Anthropic's Claude Code, consumed roughly 5,000 dollars worth of tokens, or about 50 dollars per successful hack. This was not simple automated scanning, either. In one case, after finding no weakness in a large company's public application, the agents searched digital records for associated infrastructure, found a public-facing control panel, spotted a subtle flaw in how it processed data, and after hours of trial and error tricked the server into executing malicious commands. "It's not straightforward to come up with solutions like that," Fagerland said. "It's not script kiddie stuff."

The victims' responses underline how ordinary the exposure was. Deere told Reuters it had taken "necessary remediation actions" and had "no indication that sensitive information was accessed." SharkNinja said the breach hit a standalone site carrying only product support information and that the threat was contained. Cummins said it was investigating a report involving a website operated by a third-party vendor. Reuters could not establish how much data, if any, was actually extracted, and Fagerland found other actors in the same exposed Cairn panels too, including one who stole a trove of credit card data and another who tried to direct agents to rob a cryptocurrency exchange.

For anyone building with agents, the lesson is not that a new superweapon exists. It is that the unit cost of a competent, patient intruder has collapsed, and persistence is now cheap. The same pattern Fagerland saw, a short instruction followed by a full day of unsupervised probing, is exactly how legitimate coding and research agents are meant to work. Defense has to assume that tempo: close exposed control panels and agent dashboards, patch the forgotten vendor and support sites attackers reach first, watch for long, methodical probing rather than only loud bursts, and keep human review on the actions your own agents can take. As Fagerland put it, "It's a new world now." Builders who treat agent security as a launch checklist, rather than a running cost, are going to learn that the hard way.

Rocky Mountain Madman LLC
AI Safety
Anthropic
Claude
Large Language Models
DeepSeek

Ai Industry News

DeepSeek Bets on Robot Brains, Leading Winverse AI Seed Round at a $400 Million Valuation

Cartoon illustration of a glowing robot brain hovering above a workshop robot arm learning to pick up a coffee mug while another robot watches.

DeepSeek has agreed to lead the first funding round for Winverse AI, a months-old stealth startup building artificial intelligence for robots, Bloomberg reported on October 12, citing people familiar with the matter. The seed round amounts to tens of millions of dollars and would value Winverse at about 400 million dollars after the investment. Meituan's Long-Z Investments has also committed capital, according to the reports. One caution belongs up front: the deal has not closed, and the terms and the investor list could still change.

  • Read more about DeepSeek Bets on Robot Brains, Leading Winverse AI Seed Round at a $400 Million Valuation

Britain Is Back in the Room: UK Testers Regain Access to Frontier Models, Including Gemini 4 Argon

Cartoon illustration of a robot safety inspector examining a glowing AI orb inside a glass testing chamber in a London laboratory.

Britain's AI Security Institute is evaluating the latest generation of frontier models again, including Google's Gemini 4 Argon. AI Minister Kanishka Narayan confirmed the evaluations on Monday, October 12, in a speech at Imperial College London's Base One incubator, as the government unveiled a wider package to put frontier AI to work on national cyber defences and to prepare for serious incidents involving autonomous agents.

  • Read more about Britain Is Back in the Room: UK Testers Regain Access to Frontier Models, Including Gemini 4 Argon

Cloudflare's Clef-omni: A Decision Model That Scores Text, Images, Audio, and Video in One Call

Cartoon illustration of a robot judge sorting film strips, sound waves, photographs, and documents into a single glowing funnel

Cloudflare rolled out Clef-omni on October 9, putting a new 30-billion-parameter model on Workers AI that does something most AI launches don't: it refuses to chat. Clef-omni is a decision model — it reads text, JSON, images, audio, and video in a single request and answers with calibrated probabilities over a schema of typed questions you define, with no prose and no output parsing.

  • Read more about Cloudflare's Clef-omni: A Decision Model That Scores Text, Images, Audio, and Video in One Call

Pagination

  • First page « First
  • Previous page ‹ Previous
  • …
  • Page 11
  • Page 12
  • Page 13
  • Page 14
  • Current page 15
  • Page 16
  • Page 17
  • Page 18
  • Page 19
  • …
  • Next page Next ›
  • Last page Last »

Copyright © 2026 Rocky Mountain Madman LLC - All rights reserved

Developed and Designed by Rocky Mountain Madman LLC