Unverified50% confidenceOpinionExact time
LLM training data often contains large amounts of open-source code, and generated content may imperceptibly reproduce copyrighted fragments, bringing legal risks to projects.
1
Sources
50%
Confidence
Long-term
Relevance
10/29/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedClosed-source code is one of the scarcest resources in training data; although publicly available open-source code is abundant, it cannot cover the unique patterns and security boundaries of enterprise software.72% similarUnverified潜在规避手段包括对违法训练数据施加差分隐私噪声以模糊内部表征，或将违法内容与大量正常数据混合稀释68% similarUnverifiedThe publicly available code of open-source projects makes false accusations against privacy tools easier to refute.68% similarUnverifiedMainstream large models all undergo safety alignment training before release, causing them to refuse requests such as generating malware code, assisting with cyberattacks, or producing illegal content.68% similarUnverifiedOWASP lists sensitive information disclosure as a significant risk for LLM applications, where the model may inadvertently repeat training data, system prompts, other users' sessions, or privacy fields returned by tools in its answers.67% similar
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