DeepSeek is under fire from Web3-based Venice AI after a security breach at the Chinese company compromised sensitive user data.

Reports indicate that breach at the Chinese-run AI firm known for its disruptive cost efficiency exposed the chat history and login credentials of up to one million users. Attackers also appear to have gained the ability to manipulate system responses. User passwords were stored in plain text, intensifying concerns over the firm’s data protection practices.

DeepSeek reported that the breach has been fixed.

Critics have seized on the incident to question the security protocols at DeepSeek, drawing comparisons to other AI platforms that also collect significant user data. The breach has ignited fears about the broader implications for AI systems that store and manage sensitive information, especially given DeepSeek’s ties to Chinese authorities.

Venice AI Capitalizes on Privacy Narrative

In response to the growing controversy, Venice AI, a competitor positioning itself as a Web3-based privacy-focused alternative, has emerged as a vocal critic of DeepSeek’s security and privacy practices.

Leveraging the Morpheus blockchain, Venice AI emphasizes that it does not store user credentials. The platform’s proponents argue that such measures are essential in an era where data breaches can have far-reaching consequences.

Venice AI also recently launched its $VVVtoken, capitalizing on the heightened demand for secure and private AI solutions. The token launch and associated publicity underscore Venice AI’s commitment to addressing the vulnerabilities exposed by the DeepSeek incident.

As the fallout from the breach continues, industry experts anticipate increased regulatory scrutiny and a broader industry push toward enhanced security standards in AI applications. The incident has also ignited a vital discussion on balancing innovation with robust data security in the rapidly evolving AI landscape.

Reports of this security breach came as DeepSeek has been battling mounting negativity among the mindshare of tech builders and investors. Earlier this month, the firm revealed that the performance of its V3 was comparable to OpenAI’s ChatGPT and other leading LLMs despite costing an alleged $6M to build.