Anthropic’s AI Claude escaped testing environment and hacked organizations

Company says it discovered unauthorized access during ‘proactive review’ after rival OpenAI revealed rogue agent

Anthropic ⁠said on Thursday its AI Claude model hacked ⁠systems of ⁠three ​organizations during testing, days after rival OpenAI ⁠revealed a rogue agent had gone on a days-long ⁠hacking spree at AI ​firm Hugging ‌Face.

Claude gained ‌unauthorized access to the ‌systems during cybersecurity evaluations after a misconfiguration allowed the models to reach the internet from testing environments that ‌were supposed to be isolated, Anthropic said.

The company said ​it identified the incidents after reviewing 141,006 cybersecurity evaluation runs, a process it ⁠launched following OpenAI’s disclosures.

The ‌breaches signal that AI’s expanding capabilities are already fueling the security threat experts have long feared ‌and that even top developers can be caught off-guard by flaws their models can exploit.

“Claude compromised the ​impacted ​organizations’ infrastructure using ​basic techniques, such as ​exploiting ‌weak passwords and ​unauthenticated ​endpoints,” it said.

Anthropic said the incidents involved three separate models: Claude Opus 4.7, Claude Mythos 5 and an internal research model. The earliest cases dated back to April and ‌occurred in evaluation environments that lacked what the company described as standard safeguards.

The breaches occurred during the so-called “capture the flag” exercises, in which models were tasked with finding ​hidden information in simulated networks. The company said its prompts told the models they had no internet access, but a misunderstanding with its evaluation partner Irregular left the systems connected to the public internet.

Two of the organizations were ​unaware of the activity ‌before being contacted, Anthropic ​said, adding that ​it was still trying to reach the third.

“We discovered these incidents after a proactive review of our cybersecurity evaluation transcripts,” the company said in a statement.

The findings underscore the need for stronger controls in both internal and third-party testing environments as AI models become increasingly capable of carrying out real-world cyber activities, Anthropic said.