A recent social media claim suggesting that DeepSeek's chat interface allows users to access others' historical conversations has been debunked. The issue, initially labeled as a P0-level multi-tenant isolation failure, caused widespread concern over potential privacy breaches. However, the phenomenon is actually a result of training data extraction, where the model generates content resembling real dialogue based on its training data and current system prompts, not from actual user conversations.
This behavior is common among large models and not unique to DeepSeek. Studies, including one by Google DeepMind in 2023, have shown that special inputs can trigger models to produce outputs from their training data. The inclusion of today's date in the generated content is due to the system prompt, not evidence of real-time data leakage. No proof has been found to confirm any multi-tenant isolation failure or that the outputs belong to specific users.
DeepSeek 'Bug' Misunderstood as Privacy Breach, Actually Training Data Extraction
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