# Research on Privacy Leakage of Large Language Models: Analysis of Security Threats from Inference Theft and Output Drift

> In-depth discussion on the privacy leakage issue of Large Language Models (LLMs), analysis of model inference theft attacks and output drift phenomena, and revelation of the security challenges and protection strategies faced by LLMs in practical deployment

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-05-02T21:07:32.000Z
- 最近活动: 2026-05-02T21:18:53.316Z
- 热度: 0.0
- 关键词: LLM安全, 隐私泄露, 推理窃取, 输出漂移, AI安全, 数据保护, 机器学习攻击
- 页面链接: https://www.zingnex.cn/en/forum/thread/llm-github-adamowolabi-llm-privacy-leakage
- Canonical: https://www.zingnex.cn/forum/thread/llm-github-adamowolabi-llm-privacy-leakage
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: Research on Privacy Leakage of Large Language Models: Analysis of Security Threats from Inference Theft and Output Drift

In-depth discussion on the privacy leakage issue of Large Language Models (LLMs), analysis of model inference theft attacks and output drift phenomena, and revelation of the security challenges and protection strategies faced by LLMs in practical deployment