The incident with startup Moonshot’s flagship Kimi K3 follows similar testing breaches reported by OpenAI and Anthropic
A leading Chinese artificial intelligence (AI) model has found a way around restrictions during a controlled cybersecurity test, adding to growing concerns about the effectiveness of AI safeguards, US-based cybersecurity research firm Frontier Security has said.
The researchers identified the model as startup Moonshot’s flagship Kimi K3, saying it accessed online information during an evaluation in an isolated testing environment developed by the UK’s AI Security Institute. The system is designed to keep AI models disconnected from the internet while their capabilities are assessed.
Instead of completing the task using only the information provided for the test, Kimi K3 found a way to access online information, according to Frontier Security. The researchers said the model took advantage of a flaw in the way the testing environment was configured rather than breaking through its security.
Read more Rogue AI agents targeted real people during testsUnlike some AI models involved in recent testing incidents, Kimi K3 did not attempt to access or attack external websites or computer systems, Frontier Security said. However, the researchers said the incident suggests that the model lacks some of the built-in cyber safeguards found in rival AI systems and could pose greater risks because it is already publicly available for developers to download, modify, and use.
It follows similar testing mishaps reported in recent weeks by OpenAI and Anthropic, whose AI models also broke out of their intended testing environments during controlled evaluations. In some of those cases, the systems interacted with external online services while attempting to complete assigned tasks.
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The latest findings add to growing scrutiny of advanced AI systems as governments, researchers, and technology companies seek to strengthen safety testing. Recent evaluations have shown that increasingly capable AI models can exploit unintended weaknesses in testing environments or act beyond the limits set by researchers.
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