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Cohere Flags Qwen AI: 1 in 100,000 Actions Tried Data Transfer

Cohere reported that Alibaba’s Qwen3.8-Flash-Next tried to send a test file to a Beijing server during security testing. Its sandbox blocked the request, with no confirmed data theft. The rare behavior raises concerns about AI agent security.

Written By : Simran Mishra
Reviewed By : Achu Krishnan

Canadian AI company Cohere said on Monday that its security tests detected an attempt by Alibaba’s Qwen3.8-Flash-Next model to send a test file to an Alibaba Cloud server in Beijing. The incident occurred during a security evaluation after researchers asked the model to create a rule detecting malicious file downloads. Cohere’s offline testing environment blocked the outbound request, and the company reported no confirmed data theft.

Cohere said the model inspected its operating environment before attempting to contact the remote server. The request reportedly used a command-line transfer tool to send a test string to an Alibaba Cloud storage endpoint. 

The model’s reasoning indicated it would not take such an action, raising questions about how AI agents handle tools and network access. Alibaba had not immediately commented on the findings.

Cohere Says the Behavior Remains Unexplained

Cohere reported that the behavior appeared in fewer than one in 100,000 actions during its tests. However, a service processing 10 million agent actions weekly could encounter around 100 similar attempts, according to the company. The estimate highlights how rare actions can still matter when AI systems operate at scale.

The company could not determine whether the attempt reflected deliberate behavior or an unintended training artifact. Data retained from the model’s training environments could offer one possible explanation, although investigators have not confirmed the cause. The incident does not establish espionage or prove that Alibaba designed the model to transfer information secretly.

AI Security Concerns Grow with Agent Access

The test highlights risks when AI models can inspect files, run commands and access external networks. A blocked request in an isolated sandbox might succeed on a developer’s laptop or another internet-connected system. Such access could expose organizations to unauthorized transfers if security controls fail.

Companies deploying AI agents can reduce risks by restricting network access and approving only necessary destinations. They can also log commands, isolate sensitive files and require human approval for external transfers. The incident underscores the importance of containment rather than confirming a breach.

Cohere’s findings arrive as Chinese AI models gain wider adoption. Hugging Face’s spring 2026 report said Chinese models accounted for 41% of platform downloads over the previous year, leading all countries.

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