AI hallucination of Chinese nuclear components almost led to US military attack

One source told CNN the AI-powered fiasco “almost started a war.”

some researchers suggest that it may be impossible to prevent LLMs (Large Language Models) from hallucinating altogether.

But the military’s overall use of AI seems to be accelerating.

Kyle Orland – Sep 19, 2026 , https://arstechnica.com/ai/2026/09/report-us-almost-boarded-chinese-ship-over-hallucinated-ai-arms-report/

The US narrowly avoided boarding a Chinese ship based on an “entirely false” US intelligence report generated with the help of AI tools, according to a CNN report.

That erroneous intelligence, submitted by a US Special Operations Command analyst, suggested the Chinese ship was transporting nuclear arms program components through the Middle East, according to “four sources familiar with the episode” cited by CNN. The US military was preparing to intercept and board the ship, with air support, before officials discovered a chatbot used in generating the report had “inaccurately identified the material the ship was carrying.”

One source told CNN the AI-powered fiasco “almost started a war.”

What’s the worst that can happen?

CNN’s report said the analyst in question used a chatbot to analyze intelligence reports regarding the Chinese ship’s manifest, leading to the near-disastrous result. That chatbot “fused together open-source intelligence with secret signals intelligence in government holdings,” and that information was packaged into an intelligence report that almost set off a disastrous chain of events, according to CNN.

The near-miss is one of the more potent and consequential instances of a hallucinating AI ruining the reliability of a professional report. Since “hallucinating” became the Cambridge Dictionary’s word of the year in 2023, we’ve seen prominent examples of non-fiction authors, journalists, academic researchers, judges, doctors, police departments, corporate call centers, and more getting taken in by AI tools that simply make something up when their training data doesn’t provide sufficient context. And despite some adorable attempts at “do not hallucinate” prompts, some researchers suggest that it may be impossible to prevent LLMs (Large Language Models) from hallucinating altogether.

One would hope the US military would be aware of these kinds of problems when relying on AI for analysis of intelligence reports. But the Department of Defense in January rolled out an “AI acceleration strategy” that sought to “make all appropriate data available across federated IT systems for AI exploitation, including mission systems across every service and component.”

“AI is only as good as the data that it receives, and we’re going to make sure that it’s there,” Defense Secretary Pete Hegseth said in rolling out that initiative.

Last December, the Department of Defense announced it would use Google’s Gemini for Government as the basis for its bespoke “GenAI.mil” platform. Last month, the department added Grok for Government as an option on the platform. Anthropic also offers a customized version of Claude for US spy work.

In June, a Pentagon representative bragged to Congress that they use generative AI to help create congressionally mandated reports, and that 1.5 million active DoD personnel have used the military’s generative AI tools.

In 2023, a State Department “Declaration on Responsible Military Use of Artificial Intelligence and Autonomy” stressed that “principled” use of AI by armed forces “should include careful consideration of risks and benefits, and it should also minimize unintended bias and accidents.” That report also urged that “accountable” use of AI systems must always involve “a human in the loop, a responsible human chain of command and control.”

In the years since then, though, we’ve seen fully autonomous attack drones used in the Russian conflict in Ukraine and tested by NATO-backed military contractors. In March, the Department of Defense blacklisted Anthropic over the company’s opposition to its models’ use in autonomous weapons systems, a move that a federal judge said last month was “unlawful retaliation in violation of the First Amendment.”

The reported near miss comes as extinction-level warnings from AI researchers have led to a newly prominent national conversation on AI safety, including calls for regulation and coordinated research “pacing” from leading frontier AI labs.