When AI Attacks at Machine Speed: Inside the Cairn Agent Campaign That Hit 1,200 Sites
Beginning around October 2, 2026, a Chinese-speaking threat actor deployed autonomous AI agents via the open-source penetration-testing framework Cairn to systematically target over 1,200 company websites, successfully compromising more than 100 organizations including Deere, SharkNinja, and Cummins. Operating largely unsupervised, the agents exploited web application vulnerabilities—including memcached session-store misconfigurations, unsafe PHP object deserialization, and legacy Zend Framework weaknesses—to plant persistent web shell uploaders. Successful intrusions averaged 23 hours at roughly $50 per breach, with the entire campaign costing an estimated $5,000. The exposed Cairn control panels also leaked harvested credentials and secrets, 11% of which remained valid at time of discovery. This incident marks a watershed moment in offensive AI tradecraft: for the first time, a documented criminal campaign used agentic AI at scale to autonomously discover, exploit, and establish persistence across enterprise web properties with minimal human oversight. The barrier to sophisticated, multi-target web intrusion has collapsed, demanding that defenders modernize detection and network policy enforcement to match machine-speed attacks.
Kill Chain
